Management control systems in complex settings emerging research and opportunities

Management Control
Systems in Complex
Settings:
Emerging Research and
Opportunities
Filippo Zanin
University of Udine, Italy
Eugenio Comuzzi
University of Udine, Italy
Antonio Costantini
University of Udine, Italy

A volume in the Advances in
Logistics, Operations, and
Management Science (ALOMS) Book
Series


Published in the United States of America by
IGI Global
Business Science Reference (an imprint of IGI Global)
701 E. Chocolate Avenue
Hershey PA, USA 17033
Tel: 717-533-8845
Fax: 717-533-8661
E-mail:
Web site:
Copyright © 2018 by IGI Global. All rights reserved. No part of this publication may be
reproduced, stored or distributed in any form or by any means, electronic or mechanical, including
photocopying, without written permission from the publisher.

Product or company names used in this set are for identification purposes only. Inclusion of the
names of the products or companies does not indicate a claim of ownership by IGI Global of the
trademark or registered trademark.


Library of Congress Cataloging-in-Publication Data

Names: Zanin, Filippo, 1974- editor. | Comuzzi, Eugenio, 1963- editor. |
Costantini, Antonio, 1974- editor.
Title: Management control systems in complex settings : emerging research and
opportunities / by Filippo Zanin, Eugenio Comuzzi, and Antonio Costantini.
Description: Hershey, PA : Business Science Reference, [2018]
Identifiers: LCCN 2017025774| ISBN 9781522539872 (hardcover) | ISBN
9781522539889 (ebook)
Subjects: LCSH: Industrial management. | Management science.
Classification: LCC HD31.2 .M3565 2018 | DDC 658.4/013--dc23 LC record available at https://
lccn.loc.gov/2017025774

British Cataloguing in Publication Data
A Cataloguing in Publication record for this book is available from the British Library.
All work contributed to this book is new, previously-unpublished material.
The views expressed in this book are those of the authors, but not necessarily of the publisher.
For electronic access to this publication, please contact:


Advances in Logistics,
Operations, and
Management Science
(ALOMS) Book Series
ISSN:2327-350X

EISSN:2327-3518
Editor-in-Chief: John Wang, Montclair State University, USA
Mission

Operations research and management science continue to influence business
processes, administration, and management information systems, particularly in
covering the application methods for decision-making processes. New case studies
and applications on management science, operations management, social sciences,
and other behavioral sciences have been incorporated into business and organizations
real-world objectives.
The Advances in Logistics, Operations, and Management Science
(ALOMS)  Book  Series provides a collection of reference publications on the
current trends, applications, theories, and practices in the management science field.
Providing relevant and current research, this series and its individual publications
would be useful for academics, researchers, scholars, and practitioners interested
in improving decision making models and business functions.
Coverage
• Decision analysis and decision support
• Political science
• Organizational behavior
• Risk Management
• Information management
• Operations management
• Finance
• Networks
• Services management
• Marketing engineering

IGI Global is currently accepting
manuscripts for publication within this

series. To submit a proposal for a volume in
this series, please contact our Acquisition
Editors at or
visit: />
The Advances in Logistics, Operations, and Management Science (ALOMS) Book Series (ISSN 2327-350X) is
published by IGI Global, 701 E. Chocolate Avenue, Hershey, PA 17033-1240, USA, www.igi-global.com. This series
is composed of titles available for purchase individually; each title is edited to be contextually exclusive from any other
title within the series. For pricing and ordering information please visit Postmaster: Send all address changes to above address. ©© 2018 IGI
Global. All rights, including translation in other languages reserved by the publisher. No part of this series may be reproduced or used in any form or by any means – graphics, electronic, or mechanical, including photocopying, recording,
taping, or information and retrieval systems – without written permission from the publisher, except for non commercial,
educational use, including classroom teaching purposes. The views expressed in this series are those of the authors, but
not necessarily of IGI Global.


Titles in this Series

For a list of additional titles in this series, please visit:
/>
Novel Six Sigma Approaches to Risk Assessment and Management
Vojo Bubevski (Independent Researcher, UK)
Business Science Reference • ©2018 • 251pp • H/C (ISBN: 9781522527039) • US $200.00
Enterprise Resiliency in the Continuum of Change Emerging Research and Opportunities
Raj Kumar Bhattarai (Tribhuvan University, Nepal)
Business Science Reference • ©2018 • 186pp • H/C (ISBN: 9781522526278) • US $150.00
Examining Cultural Influences on Leadership Styles and Learning From Chinese ...
Valerie Zhu (Xi’an University of Science and Technology, China)
Business Science Reference • ©2017 • 207pp • H/C (ISBN: 9781522522775) • US $125.00
Globalization and the Ethical Responsibilities of Multinational Corporations Emerging ...
Tarnue Johnson (Argosy University - Chicago, USA)
Business Science Reference • ©2017 • 110pp • H/C (ISBN: 9781522525349) • US $125.00

Multi-Criteria Decision Making for the Management of Complex Systems
Albert Voronin (National Aviation University of Ukraine, Ukraine)
Business Science Reference • ©2017 • 201pp • H/C (ISBN: 9781522525097) • US $175.00
Handbook of Research on Manufacturing Process Modeling and Optimization Strategies
Raja Das (VIT University, India) and Mohan Pradhan (Maulana Azad National Institute of
Technology, Bhopal, India)
Business Science Reference • ©2017 • 530pp • H/C (ISBN: 9781522524403) • US $285.00
Managerial Strategies and Green Solutions for Project Sustainability
Gilman C.K. Tam (Independent Researcher, China)
Business Science Reference • ©2017 • 255pp • H/C (ISBN: 9781522523710) • US $180.00

For an enitre list of titles in this series, please visit:
/>
701 East Chocolate Avenue, Hershey, PA 17033, USA
Tel: 717-533-8845 x100 • Fax: 717-533-8661
E-Mail: • www.igi-global.com


Table of Contents

Preface.................................................................................................................. vii
Acknowledgment................................................................................................xiii
Section 1
Complexity and Management Control Systems
Chapter 1
Complexity..............................................................................................................1
Chapter 2
Management Control Systems: Concepts and Approaches..................................22
Chapter 3
Management Control Systems: Contingency Factors...........................................50

Section 2
Managing Value in Complex Firms
Chapter 4
Complexity and Control: Managing for Value Creation in Complex Firms.........79
Chapter 5
Complexity and Control: Forecasting, Planning, and Budgeting in Complex
Firms.....................................................................................................................97




Section 3
Empirical Evidence of Managerial Practices in Complex Firms
Chapter 6
Strategy in Action: The Use of Visual Artefacts for Strategic Change..............131
Chapter 7
The Effect of Business Strategy and Stock Market Listing on the Use of Risk
Assessment Tools................................................................................................145
Related Readings............................................................................................... 169
About the Authors............................................................................................. 188
Index................................................................................................................... 189


vii

Preface

To reach the point that you don’t know,
you have to take the road that you don’t know.
San Giovanni della Croce (1542-1591)

WHY A BOOK ON COMPLEXITY AND
MANAGEMENT CONTROL SYSTEMS?
Theme, Perspectives, and Guidelines
“Management Control Systems in complex settings. Emerging research and
opportunities” is a relevant milestone of a research path centered around the
evocative topic of “control and firm’s value under complexity conditions”.
Complexity and control are analysed with the lens of “economic value” in
order to adopt multiple and unconventional perspectives on the topic. New
lines of reasoning have stimulated the generation of an innovative conceptual
framework that is articulated around the following turning points:
•

From the Corporate Control to the Complexity Control: This
methodological shift evokes the adoption of a new approach able
to emphasize the pivotal role of the environmental complexity for
managing firm’s value. The control of complexity becomes the
objective of the Management Control Systems (MCS) and, at the same
time, the methodological approach for controlling strategy, operations
and resources. A radical change of perspective is taking place. While
the classical approaches to management control are targeted to
maximize the financial value of the firm and its constituent assets, the


Preface

•

•

viii

complexity approach explicitly takes into consideration the active role
of the context under which management control is performed;
From the Management of Organisational Performance to the
Management of Complexity: A new conceptual framework is
proposed for managing value in complex settings. The relation between
complexity and firm’s financial performance is analysed by adopting
a new methodological perspective that encourages the exploration of
the intricate cause and effect relationships among firm’s value and its
determinants. It is difficult to develop a comprehensive understanding
of the value drivers and their impacts on firm’s value. The proposed
conceptual framework tries to overcome this imbalance by making the
causal relationships more explicit;
From the Functionalist View of MCS to the Perceived View of
Complexity Management: Traditional approaches to management
control adopt a narrow and functionalist view of the MCS.
Consequently, management control is seen as a system of formal and
analytical tools that supports rational decision-making by providing
financial measures, economic analysis and allowing “management by
exceptions”. However, decision and control processes are rarely rational
and linear. Rather, they are complex interconnections of provisional and
emerging practices that involve many actors who represent different
values, beliefs, biases and competencies. This seems consistent with
the emphasis on the individual’s perception of the importance and
use of specific MCS. Thus, MCS and complexity are not objective
entities but subjective abstractions beyond the perceived reality of
organisational phenomena. Following this line of reasoning, it is
important to make a distinction between two different conceptualisation
of complexity: perceived complexity and managed complexity. The

first conceptualization refers to complexity as a individual and social
accomplishment. The second one, draws attention to the problem of
the treatment of complexity. It depends on the degree of complexity of
the analysed problem. If the problem is simple to understand, then it
is possible to apply analytical and rational tools. Conversely, when the
problem continues to evolve over time taking unpredictable terms, it is
manageable by assuming simplifying assumptions. Then, the control of
complexity is a bundle of multifaceted practices that involves building
imperfect cognitive representations of the problem or, alternatively,
rational and computationally tractable solutions;


Preface

•

From Traditional Control Methods and Tools to Advanced Toolkit
for the Management of Complexity: Complexity management
requires the use of advanced methods and tools able to capture the
dynamics that impact on the creation, conservation or destruction
of economic value. In this perspective: a) multidimensional models
are becoming increasingly important tools for the control of firm’s
strategy in complex settings; b) there is a systematic change of the
methods and metrics that support forecasting, planning and budgeting
processes; c) increasing level of complexity stimulates the adoption
of more sophisticated measurement tools and techniques; d) advanced
management control systems combine different measurement and
representation tools (quantification, narrative approach, visual maps,
matrix, alternate templates, temporal bracketing).

THEME AND OBJECTIVES OF THE BOOK
Complexity science has emerged across different research fields in recent years.
In business management, the term complexity generally evokes a business
context involving problems in decision-making, direction, measurement and
evaluation, both by managers and stakeholders.
On the one hand, complexity implies environmental uncertainty, change,
dynamism, heterogeneity. These characteristics can be ascribed to the
contemporary competitive environment. Nowadays, firms have to face
challenges driven by a variety of factors: changes in manufacturing and
operations, the rise of emergent markets and developing economies, the
long-lasting effects of the 2008 financial crisis, evolutions in customer tastes
and preferences, relations with buyers and suppliers, rapid innovations,
variations in the actions of competitors and growing rivalry, deregulation
and globalization issues, the diffusion of information technologies.
On the other hand, firms can also be internally viewed and analyzed as
complex systems. Firms must respond to the expectations of a range of multiple
stakeholders. Product life cycles are shorter and factors such as knowledge,
innovation and intangible assets are increasing their importance. Customer
loyalty and reputation have become major concerns. Overall, complexity
influences organizational structures, and makes planning and control more
difficult.

ix


Preface

In such complex settings, firms’ efforts and abilities are oriented to formulate
and implement successful business strategies, with the purpose of creating
value for their customers and to differentiate from their competitors. In turn,

appropriate organizational devices, such as organizational design, effective
manufacturing processes, and MCS must support business strategies.
In particular, complex settings represent challenging contexts, which are
likely to require new approaches to control and MCS.
This book depicts complexity theory issues and focuses on MCS as
tools that can play a role in coping with complexity concerns to support the
attainment of strategic objectives. The objective is to provide theoretical
insights and managerial implications for managing complexity within and
across organizations.

STRUCTURE OF THE BOOK
The book consists of three sections, each with a rather different focus on both
theoretical and empirical content.
The first and second sections provide a theoretical overview about complexity
theory, management control systems and value creation, as well as strategic
issues in complex firms. In particular, the first section explores the various
approaches to complexity theory by emphasizing its multidisciplinary roots in
business management literature, examining the domain of management control
with a focus on different theoretical frameworks, conceptual constructs and
approaches. A look at contingency theory and its application to management
control systems concludes the first section of this book. The second section
covers specific items of management control, and especially managing
economic value and strategic planning in complex firms.
Finally, the third section presents the empirical results of two research
works, a qualitative case study and a survey-based quantitative study, on
emerging and innovative research themes about control in complex settings.
The volume has the following structure.
Chapter 1 provides the foundations of complexity theory as a new
perspective to address the transformative and evolutionary nature of
organizational phenomena and system dynamics. The chapter then moves from

the conceptual framework of complexity theory, which draws assumptions
and methodological implications from a variety of disciplines, to focus on its
application to business management. The effects of complexity on managerial
action are also discussed.
x


Preface

Chapter 2 delivers an overview of definitions and key concepts of
management control. Drawing from relevant academic literature, the chapter
presents some of the most popular definitions of management control,
summarizes different approaches to management control and emphasizes some
theoretical frameworks that are influencing the current debate. The chapter
depicts management control as a tool for tackling strategic and operational
issues in a highly complex business environment.
Chapter 3 covers issues regarding a fundamental theoretical approach
to MCS research, i.e., contingency theory. Based on a review of the most
prominent contingency-based research, the chapter discusses the relationships
between contingency factors and the appropriate design of MCS. In particular,
it assumes the conventional view that considers MCS as devices designed
to support managerial decision-making and summarizes the effects of
contingency variables on the design of MCS and firm performance for the
achievement of organizational objectives.
Chapter 4 focuses on managing economic value in the complex firm and
proposes a methodological framework for the analysis of complex firms, as
well as a complexity management model. The complex firm is recognized as
a coherent pattern that emerges by the combination of decisions and actions
at the levels of strategy, operations and resources. This conceptual framework
is the basis for the construction of a model for managing complexity for

business purposes. The model takes a holistic view of the firm as complex
entity and defines the managerial initiatives for copying with complexity.
Finally, the measurement of economic value under complexity conditions
is examined, with emphasis on the shift towards integrated value-based
management systems.
Chapter 5 describes forecasting, planning, and budgeting as managerial
activities involving decisions on future actions to pursue strategic objectives.
First, the chapter emphasizes the importance of complexity and its implications
regarding managerial decision-making. The discussion then moves to
forecasting, highlighting process, main methods and techniques. Next, the
chapter focuses on traditional approaches to planning, roles and limitations,
as well as alternative frameworks developed to plan under complexity. Finally,
budgeting is considered, also discussing the use of budgets in uncertain
contexts.
The empirical section comprises chapter 6 and chapter 7.
Chapter 6 presents the results of a qualitative research work. It draws on a
case study of strategy renewal in an Italian professional service firm, where
visual strategy mapping techniques were employed in a collective process of
xi


Preface

strategic decision-making. The research emphasizes that: 1) visual artefacts
reveal the complexity of strategy renewal, rather than reduce it; 2) visual
artefacts enact knowledge within strategizing processes; 3) the generated
knowledge shapes actions and meanings, hence performing strategic change.
Chapter 7 includes a survey-based quantitative study aimed at exploring
the effect of business strategy and stock market listing on the use of risk
assessment tools. The study, that is exploratory in nature, is based on a sample

of large manufacturing firms in Italy. First, drawing from academic literature,
it provides an overview of risk management as part of MCS. Then, following
a congruence approach as a form of contingency fit, two research hypotheses
are developed. To test the hypotheses and yield the results, statistical analysis
is carried out.
The range of issues addressed in this book is not exhaustive and, inevitably,
subjects of interest are omitted. However, a variety of areas are included,
delivering a picture of the relevant dimensions of complexity, management
control and their reciprocal connections.
The book is not aimed at providing prescriptive views, but it seeks to offer
insights and knowledge that may stimulate debate and further research. The
bibliography at the end of each chapter will also encourage additional study.
Filippo Zanin
University of Udine, Italy
Eugenio Comuzzi
University of Udine, Italy
Antonio Costantini
University of Udine, Italy

xii


xiii

Acknowledgment

The authors would like to thank the two anonymous reviewers for their careful
reading of the manuscript and their many insightful comments and suggestions.

Section 1

Complexity and
Management Control
Systems


1

Chapter 1

Complexity
ABSTRACT
Complexity theory provides a new perspective to address the transformative and
evolutionary nature of organizational phenomena, as well as system dynamics.
After reviewing the most influential studies of complexity science, this chapter
reflects on the application of the conceptual framework of complexity theory
on business management by providing the “3Vs model” for interpreting both
the structuralist and post-structuralist view of complexity in organizations.

INTRODUCTION
Since the open-systems view of organizations was developed, complexity has
been a term of reference and a conceptual framework for exploring social and
organizational phenomena from a post-structuralist point of view (Anderson,
1999). The science of complexity has helped to generate a great deal of
research in organization studies and has significantly advanced knowledge
in the field by developing ontological and epistemological issues that have
produced important implications for organizational theory (Tsoukas & Hatch,
2001; Allen, Maguire & McKelvey, 2011). In shifting the focus from the
reductionist to the post-structuralist perspective, two different schools of

thought on organizational complexity can be broadly distinguished. The first
one assumes that the world is objectified and conceives the organization as an
already accomplished entity, with pre-given properties that can be described,
analysed and quantified by adopting the logico-scientific mode of thought
(Bruner, 1986). Such a perspective contributes in explaining and predicting
DOI: 10.4018/978-1-5225-3987-2.ch001
Copyright © 2018, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.


Complexity

the organizational phenomena under investigation by the construction of
abstract models that provide explanations in terms of relationships among
dependent and independent variables (variance model). Consequently, the
intrinsic properties of phenomena may be discerned and it may be possible to
state common principles with predictive validity as a guide for interpretation
(Hayles, 1990). The second one employs a process perspective and tends to
conceive organizational phenomena as an emergent outcome of the process
of sense-making, through which people share meanings and interpretations
of reality. The origin of this relational ontology is the recursive relationship
among organizational phenomena, that are thought to consist of wholes
emerging out of the continuous interactivity of constituent parts, embedded
in broader wholes. Accordingly, organization is immanently generated from
within and organizational members are both observers and participants in the
unfolding of the organizational phenomena. Individual and organizational
action is performative, because it generates productive and counterproductive
effects that create and recreate the practices of the organization while the
practices enable action. The practices in which organizational members are
engaged with their knowledge, experience, values, symbols and languages
create the space for new opportunities, making organizational change

always possible (Feldman, 2003). In sum, the post-structuralist approach to
organizational knowledge views the object of study as inherently complex and,
accordingly, seeks to embrace complexity rather than reduce it. Embracing
complexity implies awareness of the need to expand the focus from the object
under investigation (the system) to include the individuals that describe the
object as complex. The integration of the two perspectives leads towards the
assumption that the features of a complex phenomenon are both objectified
descriptions and interpretations that observers assign to specific phenomena.
This assumption has important implications for how we position our approach
to organizational complexity.
Following this reasoning, the starting point for the construction of a
conceptual framework for complexity in organizational studies can be found
in four fundamental propositions:
1. Complexity can be recognised as a multidisciplinary way of thinking
about organizational phenomena, since it draws assumptions and
methodological implications from a variety of disciplines (natural
science, biology, social systems);

2


Complexity

2. Complexity is an umbrella term that encompasses a wide array of
meanings related to an assumed objective world and entirely compatible
with an interpretative approach, but distinct from complication;
3. Complexity is a constitutive trait of a system and, at the same time, a
distinct characteristic of the observer. The science of complexity sets
an initial condition: the dynamic interrelationship between the observer
and the system under investigation;

4. Complexity is a relative and relational concept, because it depends on
the perceptual filters of the observer and is generated in practice when
multiple agents interact in open-ended ways.
Although the reductionist and post-structuralist schools of thought rely
on specific methodological and theoretical assumptions, there are important
connections between them that the scientific debate has considered, in order
to explore complex ways of viewing organizations as complex systems.
Therefore, adopting a multi-perspective approach, the main objectives of
this chapter are:
•
•
•

To provide a theoretical framework that is able to investigate the
complexity of organizational and economic phenomena by adopting a
multidimensional approach;
To illustrate an alternative lens for the analysis of the firm as complex
system;
To propose an overall picture of the firm as economic value generating
system.

COMPLEXITY THEORY
Complexity science has emerged across different research fields in recent
years and various definitions of complexity can be found in literature. It is not
surprising that different views should emerge and that the attempt to explain
complexity should be conceived as an intractable problem. As one of the
foremost proponents of complexity as a new paradigm in system dynamics
remarks, no one has yet succeeded in giving a definition of complexity which
is meaningful enough to enable one to measure exactly how complex a system
is (Waddington, 1977, p. 30). Despite the fact that the scientific literature

contains a wide range of ill-defined concepts of complexity that draw their roots
from computation, biology, physics, sociology, economics and management
3


Complexity

studies, it is to be noted that entering the domain of complexity leads towards
three consolidated conceptualisations.
The first one is the recognition of two distinct ways for formulating a
definition of complex objects: state and process descriptions (Taborsky, 2014).
State description is conventional in science and focuses on the structure of
the complex object by emphasizing the number of components of a system,
as well as the number of way they can be related. Process description focuses
on the interactive relatedness of the components of a system and emphasises
the unfolding character of the interrelations over time.
The second one is the identification of five dimensions that explain a
complex system. These dimensions are proposed to be held in common by
natural, biological and social system (Tsoukas & Hatch, 2001):
•
•
•
•
•

Nonlinearity: There is no proportionality between cause and effect
relationships among constituent parts;
Scale-Dependence: There is no single measure able to capture a true
answer, because it depends on the adopted device;
Recursiveness: The repetition of the same structure at different

analytical levels of the system;
Sensitive Dependence on Initial Conditions: A variety of input
stimuli enable systems to change in an unpredictable manner;
Emergence: The essence of a system is provisional in nature, because
it is the emergent outcome of multiple chains of interactions.

Finally, the distinction between complication and complexity (Morin, 2007).
Complication comes from the Latin cum plicum, meaning with folds. The
Latin etymology of plicum refers to the fold in a piece of paper, which must
be “unfolded” in order to be observed and understood. Complex, on the other
hand, derives from the Latin cum plexum, meaning with knots, interwoven.
The Latin etymology of plexum, therefore, refers to knots, the weaving of
a cloth or a carpet, that cannot be unravelled without losing the overall
picture that it provides. The distinction produces different methodological
implications. The “complicated” approach to organizational phenomena is
analytic in nature: the phenomenon is broken down into its constitutive parts,
that are analyzed and recomposed. The “complex” approach, however, is
relational and based on emergency, aiming at providing a holistic view of
the phenomenon. Complexity arises when the different parts that constitute
a system cannot be separated, because of the recursive interrelations between
the parts and the whole, and the parts among themselves. Table 1 reports a
4


Complexity

Table 1. Complexity theory: Structuralist and post-structuralist perspectives.
Structuralist

Post-Structuralist

View

Complexity as a constitutive property of a
system

Complexity as the interactive relatedness of
emergent and nonlinear processes

Definition

Number and differentiation of parts and
irregularity of their arrangement

Intricacy of emergent processes that are
qualified by recursive interrelations and
feedback loops

Methodology

State complexity. Description of the
components of the system and their
interrelations

Process complexity. Description of the actions
that are involved in the emergent construction
of the provisional properties of the system

Tools

Analytical, rational, quantitative

Synthetic, paradoxical, qualitative

Source: The Authors

synthetic explanation of the structuralist and post-structuralist perspectives
on complexity.
The attempt to frame the most important scientific works on complexity is
a very difficult task. When a theoretical concept is elaborated using different
modes of thought, it is not surprising that different views emerge over time.
Moreover, the usefulness of this theoretical frame comes from recognizing
that the various perspectives on complexity focus on specific issues, helping
to advance our understanding of the complex and unpredictable world.
The evolution of complexity theory during the twentieth century can be
traced back to three generations of theories (Abraham, 2011; Alhadeff‐Jones,
2008).
The first generation embraces the cybernetic movement and operational
research. Cybernetics is an interdisciplinary field, born during the second
world war in the USA, where mathematics, engineers, neurobiologists,
anthropologists and social psychologists contributed to expand the possibilities
for thought and action through the elaboration of some principles like circular
and reticular causality, feedback effects and artificial intelligence. Operational
research is a field of study focusing on the elaboration of computing systems
and methods (algorithms) to support decision processes under uncertain
conditions.
The second generation encompasses computer and engineering sciences,
general system theory, system dynamics theory, studies on non-linear dynamics
and evolutionary biology. Computer and engineering sciences are involved
in the control of systems perceived as complex. By adopting sophisticated

computers, different mathematical models were elaborated and the notion
of algorithmic complexity was defined with the aim to allow a quantitative
evaluation of complexity. General Systems Theory is the European counterpart
5


Complexity

to the cybernetic movement that imposed the open system as a new approach
to social sciences. The main principles of this new approach were extrapolated
from the biology sphere, like organicism and holism. System Dynamics
Theory is a large branch of Mathematics, that had a great impact on physics,
biology, medicine and social sciences by widening the application of digital
computers. The studies on non-linear dynamics gathered together different
concepts like dissipative structure, catastrophe, chaos and fractality, with
the aim to contribute to the elaboration of frameworks for understanding the
behavior of complex systems. Finally, evolutionary biology has emerged as a
new theory on living systems, based on the concepts of evolution, adaptation,
emergence, self and autonomy.
The third generation is concerned with the studies of complex adaptive
systems and the development of epistemological reflections around the
concept of complexity. Studies on complex adaptive systems have emerged as
a multidisciplinary research collaboration for the advancement of knowledge
in the fields of natural, artificial, and social systems within the Santa Fe
Institute in New Mexico, while the epistemological debate on complexity
has constituted a conceptual research field on organized complexity that has
involved a redesign of the various concepts of complexity from the 1940s.

STUDIES OF COMPLEXITY THEORY
Drawing on these theoretical roots, researchers applied complexity theory to

the study of physical, natural, social and economic systems. The lack of an
adequate definition of complexity theory, even in the physical and natural
sciences where it was originally developed, continues to stimulate research
efforts, specifically targeted at applying concepts and methodological
implications from complexity theory to organizational issues. In management
and organizational literature, a growing number of researchers are beginning
to approach the central notions of change, evolution, adaptive and emergent
behavior with the alternative lens deriving from complexity science (Mathews,
White & Long, 1999; Allen, Maguire, & McKelvey, 2011). In shifting the
focus from a traditional approach to complexity theory for the explanation of
organizational change and transformation, it is important to explore the studies
on complexity theory that have significant implications for the advancement
in organizational and management research fields. These studies are listed in
Table 2, which shows the author, concepts and methodological implications
relied upon in each study.
6


Complexity

Table 2. Studies of complexity theory
Studies

Bohm (1951, 1980)

Asby (1961)

von Bertalanffy
(1969)
von Bertalanffy &

Sutherland (1974)
Boulding (1956,
1963)

Varela, Maturana,
Uribe (1974)

Morin (1984, 1999,
2007)

Field

Concepts

Methodological Implications

Theoretical
Physics

• The causal interpretation of quantum mechanics
as a new version of quantum theory: A system
is described in part by its wave function and it is
completed by the specification of the actual positions
of the particles.
• A new path for indeterminism, unpredictability and
application of probability in processes characterized
by chance rather than causality

Each particle of a system is
not separate or autonomous

but it is part of a timeless and
universal order

Cybernetics

• Cybernetics principles offer a scientific method for
exploring systems that are intrinsically complex.
• Parallelisms between machine, brain and society.
• Cybernetics is a prominent scientific methods for
dealing with complexity

The image of organisation as a
complex system (black box)

Biology, General
Systems Theory

• A new conceptual approach that was applied to
diverse disciplines (biology, economics, psychology,
demography) concerned with understanding open
and closed, complex, dynamic systems acting as
regulatory devices
• The approach focuses on the concept of
“open system” which emphasises the constant
interchanges of resources with the environment. This
interdependence makes the systems always open to
change.
• Other fundamental concepts include: parts/
wholes/sub-systems, system/boundary/environment,
structure/process and emergent properties

The recognition of the
multiple interrelations
between organisation and
its environment starts to
have greater relevance for
management studies.

Six keys for determining
whether or not a given system
is autopoietic

Biology and
Neuroscience

• Autopoietic organization. By drawing on biology
studies, organizations are conceived as complex
systems, qualified by reproduction and evolution. The
system is a unity that reproduces itself spontaneously
without disintegration
• Complex organization. Complexity results from
the reproduction and self-reproduction of a system
and it is influenced by the perturbations that affect
the components of the system. Each component
participates recursively in the same network of
relations which produced it.

The complex notion of
organization allows a great
advance in understanding

organizational phenomena

Philosophy and
Sociology

Definition of complexity. Many ways to understand
what complexity is.
• Irreducibility of chaos and disorder, the irruption of
irreversibility and unpredictability
• Overcoming the limits of abstraction for embracing
singularities and the embeddedness on time and space
• Complication due to the recognition of the messy
nature of the intricacies among the whole and
its constituent parts. The whole-part relationship
generates mutual implications.
• Order, disorder and organization. Order and
disorder are compatible and organization can be
related to disorder
• Organization as a complex basis, because the whole
is more and less than the sum of the parts
• Ologrammatic principle. The whole is included in
the part, the part in the whole.

continued on following page

7


Complexity

Table 2. Continued
Studies

Prigogine (1987)
Prigogine & Stengers
(1997)
Prigogine & Nicolis
(1989)

Klir & Folger (1988)

Waldrop (1993)

Le Moigne (1995)

Stacey (1995, 1996)

Arthur (1999)

Source: The Authors

8

Field

Concepts

Methodological Implications
The Newtonian-deterministic
approach is not sensitive to

irreversibility, unpredictability
and intrinsic complexity

Statistical
Mechanics
Thermodynamics

• Reconceptualization of science. From classical
perspective to complex perspective, with emphasis on
evolution, diversification and instability
• Dissipative structure. An irreversible process
(dissipation of energy) is able to play a generative role
and become a source of order.
• Open system. The growing relevance of the
recursive interactions between a system and the
environment through an entropy flow
• Equilibrium and non-equilibrium. From the isolated
system at equilibrium to non-equilibrium as a source
of order.
• Determinism and chaos. The oscillations between
equilibrium and non-equilibrium states leads towards
a stratification of determinism and chaos conditions

Computer and
system science

• Several categories of complexity, depending on
ambiguity and vagueness
• Ambiguity arises in situations where there is a oneto-many relationship between two entities
• Vagueness equals the difficulty to make distinctions

clearly

Fuzzy system dynamics
for the measurement of
uncertainty

Physics

• Conceptualization of complex adaptive systems,
based on the ability to bring order and chaos into
balance (the edge of chaos)
• Complexity depends on: relevance of
interconnections, edge of chaos, impossibility to reach
optimal solutions, coopetition and self-organization

The use of computing power
and the search for common
principles of complexity

From analytic methodology
to the design of perceived
complex phenomena

Systems theory
and constructivist
epistemology

• Conceptualization of complexity as a scientific
concept that emerges from the difficulties arising with
the rational application of the complete separability of

the observing subject and the observed object
• Complex economic systems. Economic systems are
open systems and their behavior cannot be understood
by the observer (intelligible unpredictability)
• Complexity and ambiguity. Observed object,
interpretative model and model builder form a
circular interconnection that generates ambiguity

Complexity theory as a third
perspective on the strategy
process

Management and
organizational
studies

• In complex responsive process terms, systems are
characterized paradoxically by positive and negative
feedbacks, stability and change, predictability and
unpredictability, certainty and uncertainty
• Complex systems evolve in a self-organized manner
• Complexity associated with the concepts of
variability, unpredictability, uncertainty
• Three types of change: closed (present/future as
repetition of past situations), limited (present/future
as a vague repetition of the past situations), open
(unpredictable and spontaneous change)

From equilibrium approach to
complexity economics

Economy

• Complex systems contain nonlinearities in the form
of positive feedbacks
• Complexity evolves along three fundamental
lines: natural or artificial evolution of the system
(by interaction with other systems, by increasing
the sophistication of the structure of the system, by
self-learning), knowledge exploitation (the acquisition
and stratification of knowledge allow the solution
of complex problems), power of computation and
elaboration


Complexity

COMPLEXITY MANAGEMENT
Building on the puzzle of defining the complexity of a system, some conceptual
and methodological assumptions regarding the notion of complexity can be
summarized as follows.
•

•

The importance to emphasize a concept of complexity that takes into
consideration the object under investigation and the observer. According
to a central assumption in complexity science, understanding the
complexity of a system raises issues of identification of the components
that are interconnected in such a way as to make it difficult to isolate

them (Klir & Folger, 1988). Therefore, the efforts for describing the
properties of the system that are aimed at the precise identification
of the constituent parts and their interrelations is unable to exactly
measure the complexity of a system, and the adoption of a holistic
approach is necessary (Bertuglia & Vaio, 2013). From a structuralist
point of view, the concept of complexity is used to highlight systems
that exhibit multiplicity, variety and variability of the component parts
and the relationships between them (Simon, 1996). Others use the
term complexity to indicate “…the quality of an object characterized
by various interconnected parts that make it difficult to understand its
operation” (Klir & Folger, 1988, pp. 192-193). Moreover, it is widely
recognized that complexity is a relative concept, since it depends
not only on the intrinsic properties of a system, but also on how the
system is described and interpreted by the observer (Morin, 1984;
Prigogine, 1980). The observer also can be interpreted as a complex
system, and this affects the level of perceived complexity (Casti, 1986).
Therefore, complexity is an observer-dependent phenomenon, because
it is associated with the frames of reference of the observer (that are
unique), as well as with the perceived properties of the system. This
reasoning is an interesting one, for it adds complexity, making it
difficult to uniquely define complexity as a measurable entity that can
be analyzed objectively.
The ability to use multiple approaches for understanding the complexity
of a system. Complexity is a multi-faceted phenomenon that imposes
different appropriate methods and tools (analytic, synthetic, holistic,
analogical, paradoxical, discursive), that are able to capture the
properties of the constitutive elements of the systems and their
9

Complexity

•

10

changing nature. Despite the fact that the line of demarcation between
the complicated and the complex is fuzzy, the observer can increase
his or her effectiveness in managing the complexity of the situation
under investigation by generating and accommodating a wide array
of methods and tools. The choice will depend on the degree of the
perceived complexity of the situation that the observer is attempting to
manage or to enact. To put it another way, any potential situation can
become a point of bifurcation by shifting from a low level to a high
level of complexity. In the first case, the adoption of the structuralist
approach is possible and the use of analytical tools is appropriate,
because simple and linear causal models are adequate for modelling
the system’s behaviour. In the second case, the adoption of the processbased approach is preferable and the use of analogical, paradoxical
and discursive tools is appropriate, because simple causal relationships
are inadequate for capturing the behaviour of a system with nonlinear
interconnections and feedback loops. In particular, reductions,
simplifications and approximations are required when the modelling
of complex behaviour by extrapolating regularity that emerges from
the interaction of the components of the system become intractable.
Obviously, reducing a complex system to a simpler one by abstracting
out a model is equal to compressing information by putting it into a
smaller picture that is easier to grasp.
The attempt to apply the conceptual framework of complexity theory
to business management, recognizing complexity as a structural
variable that characterizes both firms and environments. Complexity

has become a central concept in business management literature in
the 1960s, when the paradigm of the firms as open systems became
widespread. From the structuralist perspective, a complex firm can
be defined as a set of interdependent parts, which together make up a
whole that is connected to the environment in which the firm operates
(Thompson, 1967). Thus, the level of complexity of a firm equates to the
numbers of subsystems that can be identified within the organization.
Following this framework, complexity can be measured along three
dimensions (Daft, 1992): 1) vertical, that corresponds to the number
of levels in an organizational hierarchy; 2) horizontal, that refers to
the number of organizational units across the organization; 3) spatial,
represented by the number of geographical locations in which the firm
operates through subsidiaries. The complexity of the environment