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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
CONSTRUCTION RISK MANAGEMENT DECISION MAKING Explores the relevance of systems thinking and behavioral science in construction risk management Effective risk management is a vital component of all successful construction projects. Although quantitative tools for evaluating data and minimizing risk are readily available, construction managers commonly adopt a more innate, experience-based approach. In Construction Risk Management Decision Making, project manager and senior consultant Alex C. Arthur provides step-by-step advice on assessing and prioritizing risk using qualitative decision-making systems in the construction industry. Incorporating key theories and concepts from systems thinking and behavioral science, this highly practical guide focuses on the behavior patterns of real people in the industry, rather than complex quantitative techniques and data. Concise, easy-to-understand chapters highlight the current practices of construction risk management while helping readers view risk and decision making from a broader perspective. Throughout the book, the author presents invaluable insights into the ways construction professionals think and behave in the real world. * Addresses the actual risk management practices of construction professionals * Applies human behavioral theories to the study of construction risk management decision making * Illustrates the highly intuitive approaches prevalent in various construction projects * Features real-life case studies and practical examples throughout Construction Risk Management Decision Making is an excellent textbook for advanced students in project management, engineering, construction, and surveying courses, and a must-have guide for practitioners of construction management, surveying, and architecture.
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Veröffentlichungsjahr: 2021
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Table of Contents
Cover
Title Page
Copyright
Dedication
Preface
Acknowledgement
About the Author
1 Introduction – A Risk Management Approach to Construction Project Delivery
1.1 Risk Perception Categorisation
1.2 Construction Risk Data Presentation Formats
Part 1: Concepts
Overview of the Concept Chapters
2 Systems Analysis of the Construction Industry and Project Delivery
2.1 Introduction
2.2 The Construction Industry
2.3 The Construction Industry System
2.4 Construction Delivery System
2.5 The Construction Project Management System; Differentiation and Risk
2.6 Construction System's Environment and Risk
2.7 Summary
3 The Concept of Risk
3.1 Introduction
3.2 Risk Conceptualisation
3.3 Risk Etymology
3.4 Risk Conceptual Interpretations
3.5 Psychometric and Sociological Risk Perspective Application in This Book
3.6 Summary
4 Construction Risk Management
4.1 Introduction
4.2 Changing Perspectives on Organisational Risk Management Strategies
4.3 The Construction Risk Management Process
4.4 Construction Risk Management Approaches
4.5 Summary
5 Construction Risk Management Decision-Making
5.1 Introduction
5.2 The Two Systems of Thinking and Decision-Making
5.3 The Psychology of Perception
5.4 Risk Management Decision Making Under Intuition
5.5 Differentiated Risk Perceptions and Intuitive Construction Risk Management Practices
5.6 Summary
Summary of the Part 1
Part 2: Case Studies
Overview of the Part 2
6 Research Proposal, Methodology, and Design
6.1 Introduction
6.2 Research Proposal
6.3 Research Philosophical Traditions, Axioms, and Methodology
6.4 Summary
7 Data Presentation
7.1 Introduction
7.2 Case Study Project 1
7.3 Case Study Project 2
7.4 Case Study Project 3
7.5 Case Study Project 4
7.6 Summary
8 Application
8.1 Introduction
8.2 Research Proposition 1: Discussions
8.3 Research Proposition 2: Discussions
8.4 Research Proposition 3: Findings
8.5 Summary
9 Conclusions
9.1 Summary
9.2 Rethinking Construction Risk Management Practices
Appendix A: Research Design – Theory, Methodology, and Field Questions
Appendix B: Case 2 Data Presentation
B.1 Research Proposition 1: Findings
B.2 Research Proposition 2: Findings
B.3 Research Proposition 3: Findings
Appendix C: Case 3 Data Presentation
C.1 Research Proposition 1: Findings
C.2 Research Proposition 2: Findings
C.3 Research Proposition 3: Findings
Appendix D: Case 4 Data Presentation
D.1 Research Proposition 1: Findings
D.2 Research Proposition 2: Findings
D.3 Research Proposition 3: Findings
References
Index
End User License Agreement
List of Tables
Chapter 2
Table 2.1 Construction delivery system.
Chapter 3
Table 3.1 Different risk conceptual interpretations.
Chapter 4
Table 4.1 Differences between intuition and rationality.
Table 4.2 Reasons for low application of rational construction risk manageme...
Chapter 7
Table 7.1 Key facts about case study project 1.
Table 7.2 Key facts about case study 1 participants.
Table 7.3 Construction project risk events.
Table 7.4 Risk events at the pre-construction phase.
Table 7.5 Risk events at the construction phase.
Table 7.6 Risk perceptions on hypothetical project A.
Table 7.7 Risk perceptions on hypothetical project B.
Table 7.8 Consistency analysis of the risk perceptions from hypothetical pro...
Table 7.9 Analysis of perception being formed from availability and represen...
Table 7.10 Analysis of the influence of additional information (exposed heur...
Table 7.11 Effect of limited heuristics (excluding some project team members...
Table 7.12 Effect of limited heuristics (excluding some project team members) on...
Table 7.13 Consistency analysis of missed risk events.
Table 7.14 Factors influencing risk management technique preference.
Table 7.15 Level of knowledge and understanding of statistical symbols.
Table 7.16 Participants' experience with answering the quantitative and qual...
Table 7.17 The impact of probability predictions on events which evokes stro...
Table 7.18 Key facts about case study project 2.
Table 7.19 Key facts about case study 2 participants.
Table 7.20 Key facts about case study project 3.
Table 7.21 Key facts about case study 3 participants.
Table 7.22 Key facts about case study project 4.
Table 7.23 Key facts about case study 4 participants.
Chapter 8
Table 8.1 Differentiated risk perception analysis (Cross case discussion).
Table 8.2 The influence of
grounded
heuristics on the risk identification pro...
Table 8.3 The inherent subjectivity of perceptions.
Table 8.4 Missed risk perceptions.
Table 8.5 Differentiated missed risk perception analysis (Cross-case discuss...
Table 8.6 Comparison of missed risk events and differentiated risk perceptio...
Table 8.7 Level of education and training in project risk management tools a...
Table 8.8 Level of knowledge and understanding of statistical symbols.
Table 8.9 Level of knowledge and understanding of probability.
Table 8.10 Quantitative versus qualitative risk assessments.
Table 8.11 Level of indifference to events that evokes strong affective feel...
Appendix B
Table B.1 Risk events at the pre-construction phase.
Table B.2 Risk events at the construction phase.
Table B.3 Risk perceptions on hypothetical project A.
Table B.4 Risk perceptions on hypothetical project B.
Table B.5 Consistency analysis of the risk perceptions from hypothetical pro...
Table B.6 Analysis of perception being formed from availability and represen...
Table B.7 Analysis of the influence of additional information (exposed heuri...
Table B.8 Effect of limited heuristics (excluding some project team members)...
Table B.9 Effect of limited heuristics (excluding some project team members) on ...
Table B.10 Consistency analysis of missed risk events.
Table B.11 Factors influencing risk management technique preference.
Table B.12 Level of knowledge and understanding of statistical symbols.
Table B.13 Participants' experience with answering the quantitative and qual...
Table B.14 The impact of probability predictions on events which evokes stro...
Appendix C
Table C.1 Risk events at the pre-construction phase.
Table C.2 Risk events at the construction phase.
Table C.3 Risk perceptions on hypothetical project A.
Table C.4 Risk perceptions on hypothetical project B.
Table C.5 Consistency analysis of the risk perceptions from hypothetical pro...
Table C.6 Analysis of perception being formed from availability and represen...
Table C.7 Analysis of the influence of additional information on perception ...
Table C.8 Effect of limited heuristics (excluding some project team members)...
Table C.9 Effect of limited heuristics (excluding some project team members) on ...
Table C.10 Consistency analysis of missed risk events.
Table C.11 Factors influencing risk management technique preference.
Table C.12 Level of knowledge and understanding of statistical symbols.
Table C.13 Participants' experience with answering the quantitative and qual...
Table C.14 The impact of probability predictions on events which evokes stro...
Appendix D
Table D.1 Risk events at the pre-construction phase.
Table D.2 Risk events at the construction phase.
Table D.3 Risk perceptions on hypothetical project A.
Table D.4 Risk perceptions on hypothetical project B.
Table D.5 Consistency analysis of the risk perceptions from hypothetical pro...
Table D.6 Analysis of perception being formed from availability and represen...
Table D.7 Analysis of the influence of additional information on perception ...
Table D.8 Effect of limited heuristics (excluding some project team members)...
Table D.9 Effect of limited heuristics (excluding some project team members)...
Table D.10 Consistency analysis of missed risk events.
Table D.11 Factors influencing risk management technique preference.
Table D.12 Level of knowledge and understanding of statistical symbols.
Table D.13 Participants' experience with answering the quantitative and qual...
Table D.14 The impact of probability predictions on events which evokes stro...
List of Illustrations
Part 2
Figure 1 Overview of the Part 1 (concept chapters).
Chapter 2
Figure 2.1 Open system model.
Figure 2.2 Systems decomposition.
Figure 2.3 The construction project management systems.
Figure 2.4 Conceptualisation of the construction project management system....
Figure 2.5 Systems differentiation.
Chapter 4
Figure 4.1 Risk management cycle.
Figure 4.2 Risk management subsystem.
Figure 4.3 Construction risk management system.
Chapter 5
Figure 5.1 The two systems of thinking and decision-making.
Figure 5.2 Quick decision-making approach.
Figure 5.3 Gradual decision-making approach.
Figure 5.4 How perceptions are formed.
Figure 5.5 Risk management perception sub-subsystems.
Figure 5.6 Systems differentiation generating differentiated risk perception...
Chapter 7
Figure 7.1 Level of education/training in risk management systems.
Figure 7.2 Risk management techniques known by the participants (all respons...
Figure 7.3 Risk management techniques known by the participants (categorisat...
Figure 7.4 Risk management techniques applied (all responses).
Figure 7.5 Risk management techniques applied (categorisation into intuitive...
Figure 7.6 Risk management techniques preferred (all responses).
Figure 7.7 Risk management techniques preferred (categorisation into intuiti...
Figure 7.8 Trend analysis of the risk management techniques known, applied, ...
Figure 7.9 Trend analysis of the risk management techniques known, applied, ...
Figure 7.10 Risk management data presentation formats known.
Figure 7.11 Risk management data presentation formats known (categorisation ...
Figure 7.12 Risk management data presentation formats applied.
Figure 7.13 Risk management data presentation formats applied (categorised i...
Figure 7.14 Risk management data presentation formats preferred.
Figure 7.15 Risk management data presentation formats preferred (categorised...
Figure 7.16 Trend analysis of the risk management data presentation formats ...
Figure 7.17 Trend analysis of the risk management data presentation formats ...
Figure 7.18 Risk events certain to occur.
Figure 7.19 Risk event certain not to occur.
Figure 7.20 Risk event certain to have the highest impact.
Figure 7.21 Assessment of participants' understanding of quantitative probab...
Figure 7.22 Assessment of participants' understanding of qualitative probabi...
Chapter 8
Figure 8.1 Cross-case trend analysis of the known, applied, and preferred ri...
Figure 8.2 Cross-case trend analysis of the known, applied, and preferred ri...
Appendix B
Figure B.1 Level of education/training in risk management systems.
Figure B.2 Risk management techniques known by the participants (all respons...
Figure B.3 Risk management techniques known by the participants (categorisat...
Figure B.4 Risk management techniques applied (all responses).
Figure B.5 Risk management techniques applied (categorisation into intuitive...
Figure B.6 Risk management techniques preferred (all responses).
Figure B.7 Risk management techniques preferred (categorisation into intuiti...
Figure B.8 Trend analysis of the risk management techniques known, applied, ...
Figure B.9 Trend analysis of the risk management techniques known, applied, ...
Figure B.10 Risk management data presentation formats known.
Figure B.11 Risk management data presentation formats known (categorisation ...
Figure B.12 Risk management data presentation formats applied.
Figure B.13 Risk management data presentation formats applied (categorised i...
Figure B.14 Risk management data presentation formats preferred.
Figure B.15 Risk management data presentation formats preferred (categorised...
Figure B.16 Trend analysis of the risk management data presentation formats ...
Figure B.17 Trend analysis of the risk management data presentation formats ...
Figure B.18 Risk events certain to occur.
Figure B.19 Risk event certain not to occur.
Figure B.20 Risk event certain to have the highest impact.
Figure B.21 Assessment of participants' understanding of quantitative probab...
Figure B.22 Assessment of participants' understanding of qualitative probabi...
Appendix C
Figure C.1 Level of education/training in risk management systems.
Figure C.2 Risk management techniques known by the participants (all respons...
Figure C.3 Risk management techniques known by the participants (categorisat...
Figure C.4 Risk management techniques applied (all responses).
Figure C.5 Risk management techniques applied (categorisation into intuitive...
Figure C.6 Risk management techniques preferred (all responses).
Figure C.7 Risk management techniques preferred (categorisation into intuiti...
Figure C.8 Trend analysis of the risk management techniques known, applied, ...
Figure C.9 Trend analysis of the risk management techniques known, applied, ...
Figure C.10 Risk management data presentation formats known.
Figure C.11 Risk management data presentation formats known (categorisation ...
Figure C.12 Risk management data presentation formats applied.
Figure C.13 Risk management data presentation formats applied (categorised i...
Figure C.14 Risk management data presentation formats preferred.
Figure C.15 Risk management data presentation formats preferred (categorised...
Figure C.16 Trend analysis of the risk management data presentation formats ...
Figure C.17 Trend analysis of the risk management data presentation formats ...
Figure C.18 Risk events certain to occur.
Figure C.19 Risk event certain not to occur.
Figure C.20 Risk event certain to have the highest impact.
Figure C.21 Assessment of participants' understanding of quantitative probab...
Figure C.22 Assessment of participants' understanding of qualitative probabi...
Appendix D
Figure D.1 Level of education/training in risk management systems.
Figure D.2 Risk management techniques known by the participants (all respons...
Figure D.3 Risk management techniques known by the participants (categorisat...
Figure D.4 Risk management techniques applied (all responses).
Figure D.5 Risk management techniques applied (categorisation into intuitive...
Figure D.6 Risk management techniques preferred (all responses).
Figure D.7 Risk management techniques preferred (categorisation into intuiti...
Figure D.8 Trend analysis of the risk management techniques known; applied a...
Figure D.9 Trend analysis of the risk management techniques known; applied a...
Figure D.10 Risk management data presentation formats known.
Figure D.11 Risk management data presentation formats known (categorisation ...
Figure D.12 Risk management data presentation formats applied.
Figure D.13 Risk management data presentation formats applied (categorised i...
Figure D.14 Risk management data presentation formats preferred.
Figure D.15 Risk management data presentation formats preferred (categorised...
Figure D.16 Trend analysis of the risk management data presentation formats ...
Figure D.17 Trend analysis of the risk management data presentation formats ...
Figure D.18 Risk events certain to occur.
Figure D.19 Risk event certain not to occur.
Figure D.20 Risk event certain to have the highest impact.
Figure D.21 Assessment of participants' understanding of quantitative probab...
Figure D.22 Assessment of participants' understanding of qualitative probabi...
Guide
Cover
Table of Contents
Title Page
Copyright
Dedication
Preface
Acknowledgement
About the Author
Begin Reading
References
Index
End User License Agreement
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Construction Risk Management Decision Making
Understanding Current Practices
Alex C. Arthur
This edition first published 2022
© 2022 John Wiley & Sons Ltd
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.
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Library of Congress Cataloging-in-Publication Data
Name: Arthur, Alex C., author.
Title: Construction risk management decision making : understanding current practices / Alex C. Arthur.
Description: Hoboken, NJ : Wiley-Blackwell, 2022. | Includes bibliographical references and index.
Identifiers: LCCN 2021039340 (print) | LCCN 2021039341 (ebook) | ISBN 9781119693000 (hardback) | ISBN 9781119692997 (adobe pdf) | ISBN 9781119693024 (epub)
Subjects: LCSH: Construction industry–Risk management. | Decision making.
Classification: LCC HD9715.A2 A78 2022 (print) | LCC HD9715.A2 (ebook) | DDC 624.068/1–dc23
LC record available at https://lccn.loc.gov/2021039340
LC ebook record available at https://lccn.loc.gov/2021039341
Cover Design: Wiley
Cover Images: © Stitchik/Getty Images
To my dearest mum, Mama Alice Felicia Arthur, and my beloved son, Alex Collins Arthur Jnr (aka Xander)
Mum, the inspirational words that you said to me at the tender age of 10 have stayed with me and given me the confidence to pursue excellence. I will always treasure those words.
Xander, you have given me a sense of accomplishment since you came into my life.
Preface
There are extensive psychometric research and publications that confirm the influence of behavioural stimulus in intuitive risk management decision-making systems (Kahneman and Tversky 1982a; Tversky and Kahneman 2002; Finucane et al. 2003; Slovic 2010; Kahneman 2011). The existing construction management publications however appear limited in exploring the behavioural patterns underpinning the high incidence of intuitive construction risk management practices. The purpose of this book therefore is to address the data gap, by extending current empirical and analytical evidence from systems thinking and behavioural sciences into construction risk management research, to strengthen their theoretical basis and further illuminate emerging theoretical extensions.
The empirical findings from four case qualitative research methodology have revealed substantial evidence in support of three theoretical propositions: risk perception categorisation within the construction project delivery system reflecting the structure of the differentiated specialist roles, psychological difficulties associated with intuitive risk identification of events outside the scope of our heuristics, and incompatibilities of mixing decision processing approaches and data presentation formats from different systems of thinking and decision-making.
The subsequent analytical discussions have highlighted the need to rethink construction risk management practices, by introducing behavioural science training to construction project management students and professionals. This will equip them with the requisite competencies to identify and harmonise the different affective heuristics, as well as the technical variations of the specialist roles involved in project delivery. There is also the need to consider revising construction risk data presentation from statistics and probability to qualitative formats to complement the current intuitive construction risk management decision-making practices.
Acknowledgement
I am thankful to God for granting me wisdom and insight throughout the book project.
I would also like to pay tribute to my former doctoral supervisor, the late Professor Emeritus Stephen D. Pryke, for his tremendous influence on the development of my initial research ideas. I must also mention the support received from the lecturers and staff of the Bartlett School of Construction and Project Management, University College London, especially Professor Hedley Smyth.
Furthermore, I wish to express my sincere gratitude to my dear parents, Mr and Mrs Arthur, my wife, Mrs Rubina F. Arthur, my beloved son, Alex Collins Arthur Jr, and all my siblings for their love and support.
Lastly, I would like to thank the directors and staff of the organisations that participated in the data collection processes, for the Part 2 case studies.
About the Author
Dr Alex C. Arthur, BSc MSc PhD FRICS MAPM is a chartered project management surveyor with more than 14 years' experience working in multidisciplinary practices. He is a Fellow of the Royal Institution of Chartered Surveyors (RICS) and an examiner of their Assessment of Professional Competency (APC) programme. He is also a member of the Association of Project Managers.
Dr Arthur is a certified professional teacher and postdoctoral researcher who possesses extensive research and industrial expertise within the United Kingdom and other international construction industries. He has published a number of articles, journals, and contributions to books on systems thinking and analysis, intuitive decision-making, intuitive construction risk management systems, construction risk management decision-making systems, partnering procurement, development control, and planning systems.
1Introduction – A Risk Management Approach to Construction Project Delivery
Hazard and uncertainty have always been a part of human condition (Lock 2003; Beck 2007). The early humans at pre-civilization faced the daily challenge of protecting themselves against attacks from wild animals and hostile tribes. The modern society may have developed remedies against those threats, but there are equally other factors that threaten our persistence, like the ongoing Covid-19 pandemic. The emergence of vaccines has provided glimmers of hope that we may be heading towards the end of the pandemic. The fact however remains that there will always be other natural and social menace that challenges human survival.
Social hazards and uncertainties were conventionally defined and managed by the religious and political leaders occupying the top of the vertical social structure. This was done through the reliance on guided morality, superstition, taboos, and rituals (Japp and Kusche 2008). The contemporary transition of multiple differentiated functional subsystems replacing the stratified vertical system has expanded social risk communication into the public realm (Japp and Kusche 2008). According to Loosemore et al. (2006), the increased public awareness on the risk variables associated with both personal and corporate activities and increased media reportage on the impact of risk events have accounted for the heighten discussions on risk and influenced public attitude to risk management. A failed suicide bomb attack in which the perpetuators planned to detonate liquid explosives on several aircrafts traveling from Heathrow Airport to the United States of America in 2006 led to public discussions on the risk posed by liquids on aircrafts, resulting in a European Union imposition of restrictions on carrying liquids on aircrafts, which subsequently has become a world-wide ban. The use of Blackberry Instant Messenger system to elude police intelligence by the perpetuators of the August 2011 British riots triggered public discussions on the security risk associated with smart phones (The Economic Times 2011).
In the context of construction delivery, the catastrophic demise of a 6-year-old girl at Carnival Place, Moss Side, Manchester, United Kingdom on 28 June 2010, and a 5-year-old girl at Brook Court, Bridgend, South Wales, United Kingdom on 3 July 2010, after they became trapped in electric gates, coupled with two other near misses in July and September 2010, ignited public debates on the safety of electric door entry systems. The result was the formation of the Gate Safe charity in 2010, to promote safety guidance for the construction of automatic and manual gates (Gate Safe 2020). The 2017 Grenfell Tower fire incidence in the United Kingdom has also stimulated public discussion on the fire safety risks associated with high rise buildings (Arthur 2017). The immediate impact has been a public inquiry and enactment of changes to the statutory building regulations. The heightened public risk communications have cumulatively increased construction clients' awareness of the typical industry risk events, with the expectation of their management through the project delivery processes. The control of project risk is now seen as being synonymous with the control of the project itself (Pryke and Smyth 2006; Abderisak and Lindahl 2015), which in effect establishes a direct relationship between effective risk management systems and project success (Cagno et al. 2007).
Risk as explained by Loosemore et al. (2006) is an uncertain event that might occur in the future, to potentially affect an interest or objective (usually adversely), although the precise likelihood or impact may be indeterminate. The theoretical emphasis is the relationship between risk and uncertainty and probability judgement. It also emphases risk as a future potential occurrence with the propensity to impact on an objective or interest.
Loosemore (2006) has also described risk management as a field of competing ideologies between the homeostatic and callibrationist perspectives (Hood and Jones 1996). The homeostatic perspective proposes scientific approach to risk management through structured risk identification and rational decision-making, whilst the callibrationist viewpoint believes in human subjectivity in risk interpretation, identification, and treatment (Loosemore 2006). Another significant ideology of the callibrationist view is the subjectivity and biases of the personal perceptions responsible for guiding the risk identification and treatment processes (Tversky and Kahneman 1982a,b,c; Kahneman and Tversky 1982a,b; Slovic 2010; Kahneman 2011). Japp and Kusche (2008) theorisation of social construction of risk through the communicative and decision-making processes of multiple differentiated functional subsystems and the ensuing analytical variability in social risk interpretations give the callibrationist approach an edge over the homeostatic method in the management of risk within the contemporary era.
This book has therefore adopted theories and concepts from systems thinking and behaviour sciences in demonstrating the social construction of risk (Zinn 2008) and the subjectivity of risk perceptions (Slovic 2010; Kahneman 2011). The principles of general systems theory (Bertalanffy 1968, 2015) have enabled conceptual analysis of the risk management subsystem within the construction project delivery system. The concept of systems differentiation (Walker 2015) and the existing empirical evidence on the psychology of perception (Slovic 2010; Kahneman 2011) have been applied in analysing the pattern of risk perceptions emanating from the different specialist roles responsible for design development and risk management decision-making, including the project manager, contracts manager, technical manager, architect, engineer, quantity surveyor, and client. The emphasis on design development is due to the close relationship between design concepts and the generation of project risk events (Latham 1994; Egan 1998; Lock 2003; Flyvbjerg et al. 2003). According to Bea (1994), the bulk of the initial project design errors later results in risk events, with approximately 42% and 50% actualising during the construction and operational phases, respectively.
The ensuing analytical review has resulted in the discovery of a new theoretical interpretation for risk perception categorisation based on the differences in affective heuristics of the different specialist roles within the construction project delivery system. The theoretical evidence has been further confirmed through a four case qualitative empirical research investigation covered in the Part 2. There has been further theoretical discussion on the risk management decision-making subsystem within the construction project delivery system, to examine the impact of mixing tools and techniques from different systems of thinking and decision-making (Walker 2015; Kahneman 2011). The resulting analytical review and subsequent empirical findings have also confirmed the psychological difficulties in mixing risk management approaches and data presentation formats, from the rational and intuitive decision-making subsystems.
1.1 Risk Perception Categorisation
The need for a robust explanation for the differences in risk perceptions becomes imperative when we consider the contemporary construction management research findings which reveals high incidence of intuitive risk management practices (Akintoye and Macleod 1997; Lyons and Skitmore 2004; Kululanga and Kuotcha 2010), fuelled by perceptions (Slovic et al. 2010). The inherent subjectivities of perceptions (Bateman et al. 2010) suggests that a failure to adequately identify the sources and structure of the risk perception components within a construction project delivery system may affect the effectiveness of the risk identification and treatment processes, and ultimately, project success (Pryke and Smyth 2006; Cagno et al. 2007).
The quest for a novel theoretical explanation for risk perception categorisation also stems from the fact that the present theories and concepts which discusses the subject, including differences in personality traits (Weber and Milliman 1997; Smith et al. 2006; Chauvin et al. 2007), prospect theory (Kahneman and Tversky 1979; Kahneman 2011), differences between project team members and external stakeholders (Loosemore et al. 2006), and culture theory (Thompson et al. 1990) have been criticised for lacking adequate explanation for the complex risk perception categorisations within the internal structure of the construction project delivery system.
1.1.1 Differences in Personality Traits
Weber and Milliman (1997), Smith et al. (2006), and Chauvin et al. (2007) argue that differences in risk perceptions arises from the differences in individual personality traits. Other research findings have, however, identified inconsistencies in risk perception categorisation for the same individual for studies where different methods were used (Slovic 1964; MacCrimmon and Wehrung 1990), and also studies where the same method was applied under different circumstances (Schoemaker 1990; MacCrimmon and Wehrung 1990).
1.1.2 Prospect Theory
Prospect theory (Kahneman and Tversky 1979; Kahneman 2011) proposes that people generally are risk averse with a preference for prospects that offer certainty in gain, and a dislike for mixed prospects composed of probabilities for gains and losses. Prospect theory has been criticised for failing to explain the factors which influences preference reversals (Slovic and Lichtenstein 1983, p. 582) and the discrepancies in an individual's risk preference under domains of certainty, and probability, experienced in similar risky scenarios (Schoemaker 1990).
1.1.3 Differences Between External Stakeholders and Project Team Members
Loosemore et al. (2006) identifies differences in risk perceptions at the construction project delivery system between the external stakeholders and the project team members. The broad categorisation appears too simplistic and falls short of an explanation for the differences in perceptions within the project team and external stakeholder subsystems. The fact that in practice, final risk management analysis and decision-making are executed by project team members and not external stakeholders (Lyons and Skitmore 2004) may explain the differences in exposure and perceptions.
1.1.4 Culture Theory
Culture theory proposes that people form groups based on common objectives, values, and perceptions (Thompson et al. 1990). The differences in risk perceptions therefore exist along the institutions and associations within the social setup. Kamper (2000) has, however, criticised culture theory for failing to explain the complex internal structures of the institutions and subgroups within the larger society.
1.2 Construction Risk Data Presentation Formats
The theoretical evidence on systems differentiation (Walker 2015) and systems decomposition processes (Carmichael 2006) confirms the presence of micro differences in objectives within systems components. This in turn suggests differences in how the internal parts experience and respond to the impact from their environmental forces (Loosemore et al. 2006). The implications being that mixing tools and techniques from different decision-making systems, as evident in the present construction risk management practice of intuitive processing of statistical and probability data (Akintoye and Macleod 1997; Lyons and Skitmore 2004; Kululanga and Kuotcha 2010; Bowden et al. 2001; Lock 2003) may introduce conflicting responses which may impede the required collaborative transformational processes, thereby producing systemic errors (Kahneman 2011). The ensuing theoretical issues and psychological concerns have been analysed in the Part 1 and further validated through the case study empirical investigations presented in the Part 2.
Part 1Concepts
Overview of the Concept Chapters
Figure 1 provides an overview of the Part 1 (Chapters 2–5), which discusses the key concepts and theories covered in the book.
Figure 1 Overview of the Part 1 (concept chapters).
2Systems Analysis of the Construction Industry and Project Delivery
2.1 Introduction
Chapter 2 begins the conceptual review. Taking a social construction approach to risk interpretation, the principles of systems thinking and analysis are applied in discussing the construction industry; internal structure, transformational processes, and the interactions with the wider environment, leading to risk generation. The chapter starts with an exposition of the UK construction industry, its contribution to the national economy and government's aspiration to reduce project capital cost, whole life costing, and construction period. The government has also set targets for reduction of greenhouse gas emission in the built environment, and the trade gap between export and importation of construction products and materials. The high standard industry aspirations call for efficiencies in the project management and operational systems, including risk management practices.
The chapter then proceeds to review some key principles of general system theory including open systems whose operations involve interactions with the other systems and subsystems within the wider industry environment, and closed systems which are self-containing entities, able to function independent of external influences. The constant interactions of the human and material resources within the construction industry accordingly confirms its classification as an open system. There is also theoretical review of systems objectives which defines the required inputs, transformational processes, and outputs. The subsequent analytical review of the internal structure of the construction system, using the concept of systems decomposition, reveals the core components comprising of different specialist roles, department, organisations, and sectors providing the human resources; different operational phases and stages for the product delivery; and different tools and techniques applied in the conversion of construction materials and resources into the final products.
The theoretical review continues with the examination of the construction delivery system through the RIBA Plan of Work 2020 stages. The input of a stage is generated from the output of the preceding stage and the wider construction industry environment. The transformational processes apply construction industry tools and techniques to convert received inputs into expected outputs, for the subsequent delivery stages and the wider construction industry environment.
The construction delivery system involves constant interactions of different specialist roles with different functionalities. The failure to carefully coordinate the multifaceted communications often leads to cross-purpose working, and subsequently, inhibition to the achievement of systems' objectives. The concepts of systems differentiation and decomposition have been utilised in a theoretical review of the ramifications, which also establishes the relevance of the project management role. The subsequent discussions analyse how the factors responsible for systems differentiation also introduces variability into the construction management and operational structures. The failure to manage these differences often results in the creation of risk events.
The chapter ends with an evaluation of the construction system's environmental forces comprising the political functional subsystem, economic functional subsystem, socio-cultural functional subsystem, technological functional subsystem, ecological functional subsystem, and legal functional subsystem. The bilateral interactions between the differentiated functional environmental forces and the construction system, which is also made up of differentiated specialist roles, often result in the social construction of risk. This manifests in the form of differences in risk interpretations and responses of the construction project coalition.
2.2 The Construction Industry
The construction industry forms the bedrock of most national economies. The industry is responsible for the construction, repair, and management of building stocks and associated activities including civil engineering constructions and specialist installations.
The United Kingdom's Office of National Statistics publication released on 18 October 2019 reported 325 736 registered firms in the construction industry (Allcoat 2018). The Industrial activities excluding the professional services firms contributed £117 billion and 2.4 million jobs to the national economy in 2019, which represented 6% of the national gross domestic product (GDP) and 6.6% of all employment, respectively (Rhodes 2019). The industry received £61.7 billion new orders in 2018 comprising of £21.6 billion (35%) for housing projects, £15.2 billion (25%) for commercial projects, £11.5 billion (19%) for infrastructure projects, £8.2 billion (13%) for public projects excluding housing and infrastructure, and £5.1 billion (8%) for industrial projects (Rhodes 2019).
The UK governments' policy aspirations for the construction industry as expressed in the Construction 2025 policy document includes 33% reduction in project capital cost and whole life cost; 50% reduction in construction period for both new build and refurbishment of the existing building stock; 50% reduction in greenhouse gas emission in the built environment; and 50% reduction in the trade gap between the export and importation of construction products and materials (Rhodes 2019). It is obvious that achievement of the policy aspirations will require project management and operational efficiencies including robust risk management systems.
2.3 The Construction Industry System
Construction delivery involves the management of human and material resources to produce houses, schools, industries, hospitals, public buildings, roads, and bridges to serve human needs. There are also statutory and operational policies that regulate construction activities. The construction delivery process goes through different stages where human and material resources are transformed into finished construction products. This has led to some construction management researchers such as Walker (2007, 2015) arguing similarities between the construction delivery process and the principles of systems thinking and analysis.
A system is a set of related variables which function together as a group, and in the process, displays the prime attributes of the collective group instead of the individual components (Checkland 1999). Systems thinking and analysis on the other hand is an investigative approach to studying a subject by adopting the principles of classical natural sciences (Checkland 1999). The underlining principles originated from the biological sciences, through the discovery of the general systems theory in the 1960s (Walker 2007, 2015; Bertalanffy 1968, 2015). This occurred at a time when Ludwig Von Bertalanffy was investigating the linkages between the different science disciplines, which hitherto were studied as distinct subjects. Bertalanffy has suggested that the application of the principles of systems thinking pre-dates the discovery of the general systems theory, and may have been applied in earlier studies including Paracelsus' research in medicine, and Leibniz's studies in philosophy, although the term ‘system’ may not have been specifically mentioned. Arthur (2020) has also argued the application of systems analysis in the Christian Holy Bible narratives, as seen in Apostle Paul's comparison of the Christian mission to the corporate functioning of the different human body parts (Romans 12:4–8; 1 Corinthians 12:12–31). The ideologies of systems thinking and analysis are not only limited to the classical natural sciences but could also be applied in other disciplines to investigate the networks and interactions between the sub-modules. Checkland (1999) has therefore suggested that systems thinking and analysis should be interpreted as a methodology for studying a subject, rather than as a distinct discipline.
2.3.1 Open and Closed Systems
Systems are categorised as ‘closed’ or ‘opened’ depending on how they relate to their surrounding (Bertalanffy 1968, 2015). Closed systems analytically are self-containing, as they do not respond to forces within their surrounding (Cole 2004; Cole and Kelly 2020). The implication being, they are unable to accommodate environmental changes which conflicts with their design and internal processes. Walker (2015) argues that machines are closed systems in that they are designed with specific components and prescribed functionalities independent of the changes in their environment. Contemporary technological innovations, however, have enabled some machines with in-built regulatory mechanisms to adjust their operations in line with the changing conditions in their environment. An example is the thermostatic controls in fridges which are programmed to regulate the machines' internal temperature based on their external heat condition. In practice, living subjects do interact with their environment (Walker 2015) implying that, the concept of a closed system exists more in the rhetoric rather than in reality. A closed system's analytical approach to studying a subject focuses mainly on the network of interactions within the internal structure without exploring the linkages and communications between the subject and its environment (Walker 2015; Bertalanffy 2015).
Figure 2.1 Open system model.
Sources: Adapted from Cole (2004), Cole and Kelly (2020), and Walker (2015).
An open system on the other hand is active and adaptive to changes within its environment (Cole 2004; Cole and Kelly 2020; Wetherbe and Vitalari 1994). Cole and Kelly (2020) has suggested the key characteristics of an open system as receiving inputs or energy from its surrounding, converting the inputs into outputs, and subsequently discharging the output back into its environment.
An open system's analytical approach to studying a subject incorporates both the interactions within the system's internal structure and processes and the networks and linkages within the wider environment (Walker 2015). The networks and interactions result in the conversion of inputs from the environment through the system's internal transformation processes into outputs to serve the other systems within the wider environment (see Figure 2.1).
In practice, living subjects exhibit open system characteristics by taking their energy from their environment and using their internal transformational processes to convert into outputs to serve the other systems within their environment (Mullins 2005). An example of an open system is automobile vehicles that receive inputs in the form of fuel, lubricants, and coolant from the petroleum and vehicle consumable industries, and then converts through their internal mechanisms into energy to propel the vehicles in transporting human and other resources from the other systems within its environment. Likewise, the construction industry as an open system receives inputs in the form of specialist skills and material resources from its environment, and then converts through the application of industry managerial and operational principles, into construction outputs such as residential dwellings, offices, industries, roads, bridges, hospitals, schools, commercial outlets, and airports, for the benefit of the other systems within the wider environment. Wetherbe and Vitalari (1994) have argued that few systems in reality behave exclusively as opened or closed. Most systems function in a continuum between the two extremes.
2.3.2 Construction System Objective
According to Walker (2015), every system has an objective which describes what it exists to achieve. A system's objective therefore can be likened to a ship compass responsible for navigating the ship's nautical charts from the departure port to the destination. And as a navigator, any new information which cause changes in the nautical positioning will result in a corresponding change in direction. This suggests that objectives rather than being static are dynamic and responsive to changes in system's environmental forces (Winch 2010).
Construction systems' objectives similarly are responsible for directing the integrated human and material resources from project inception, through the different transformational phases, to the desired outputs. Cole (2004) has suggested differences in construction systems objectives at the strategic and operational levels. The strategic objectives define the broad overall organisational mission statements and long-term business strategic aims, whilst the operational objectives outline the individual project expected output (Carmichael 2006).
Construction systems' objectives also function as parameters for monitoring and appraising performance at both the strategic and operational levels (Lock 2003). Appraisal at the operational level occurs at the interim delivery phases and overall completion stage. Project execution outputs are constantly evaluated against the contemporaneous project objectives at the different delivery phases, before progressing to the next phase. When a project achieves completion, the final product is assessed against the project brief to establish success or failure. The effectiveness of a construction system's objective in assessing project performance largely depend on it being clearly defined, to avoid ambiguity in interpretation and application.
Walker (2015) has argued that, construction project objectives are generated as a response to demands from client organisational stakeholders, comprising customers, employees, shareholders, suppliers, communities, and related statutory authorities. Cova and Salle (2006) have also classified organisational stakeholder groups into business actors and non-business actors. The business actors consist of consultants, agents, project financers, sub-consultants, and sub-contractors. The non-business actors are also made up of government organisations regulating construction activities, construction trade unions and pressure groups, syndicates, lobbies, and activists.
The analysis of stakeholder demands within the framework of client organisational business objectives usually results in responses ranging from construction of a new project, refurbishment or extension of an existing construction asset, outsourcing additional building space through direct purchase, leasing, or renting (Winch 2010). This applies to both clients whose core business activities involves the provision of construction products and also clients who require construction products to support their core business activities. As an illustration, a residential property developer will most likely commence a new development when there is evidence of demand for housing within its areas of business activities, either in the form of increased applicants on its waiting list or improved economic activities which draw in additional potential customers. In the same way, a supermarket will extend or build a bigger shop when there is increase in its customer base.
2.3.3 Construction System's Components and Decomposition
An open system comprises individual interdependent parts which are referred to as subsystems. It is possible to analyse construction system components from the broader industry organisational level, where the parts comprise of contributors from client, contractor, and consultant organisations. Similarly, we can analyse the construction systems components at the project organisational level in the context of the tasks and processes involved in project delivery (Walker 2015).
According to Carmichael (2006), open systems exist within their wider environment as subsystems interacting with allied subsystems to define the boundaries of their superior main system. The multiple related open systems subsequently become the components of the superior main system. Applying the principles of systems thinking correspondingly enables analysis of the components of the subsystems, as sub-subsystems with parts interacting to define the boundaries of the respective subsystems. The micro parts can be further analysed as sub-sub-subsystems also exhibiting general systems properties. The process could be continued in a linear progression to give an analysis of systems decomposition.
The application of systems decomposition at the construction industry organisational level as depicted in Figure 2.2 identifies the different client, contractor, and consultant organisations, which collectively forms the construction industry's system. Within the three broad classifications are subsystems which could be categorised based on their geographical locations, scope of core business activities, type of business ownership, level of experience, and type of services and products. Narrowing it down to the individual companies and firms are devolved organisational structures in the form of departments and teams which could be analysed as sub-subsystems. The departments and teams further devolve into lower organisational structures of programmes and projects. The multiplicity of categorisations within the client, professional consultancy, and building contractor organisations and the ensuing lower tier micro systems, coupled with the varied interactions existing between the components, suggest the construction systems decomposition analysis could be complex than the simplistic model depicted in Figure 2.2.
Systems decomposition at the construction project organisational level can also be analysed through the categorisation of project objectives as subsystems. The various transformational processes and tasks responsible for the achievement of the different objectives become sub-subsystems. The required activities within the various transformational processes and tasks subsequently become the sub-sub-subsystem.
2.4 Construction Delivery System
The construction system goes through various processes, in converting inputs received from the environment into outputs which are released back to the wider environment, to be used as inputs by other systems (Walker 2007). The RIBA Plan of Work 2020 identifies eight stages of construction delivery including strategic definition, preparation and briefing, concept design, special coordination, technical design, manufacturing and construction, handover, and use (RIBA 2020).
The first stage of the RIBA Plan of Works is strategic definition, which involves the preparation of outline client requirements. The key inputs at this stage are the client organisation's mission and vision statements responsible for defining their business activities. The development of a project business case serves as a guide in evaluating alternative development proposals, to ascertain viability in the context of the defined outline client requirements. The options appraisal may also include site appraisals and desk analysis of the project benefits and constraints, potential risk events, and project budget, leading to the establishment of a favourable development proposal.
Figure 2.2 Systems decomposition.
Source: Adapted from Carmichael (2006).
The second stage of the RIBA Plan of Works centres on the preparation of project brief. This involves feasibility studies of the favourable development proposal established in the preceding stage, using site survey results and existing documentation. The client may appoint a design team comprising of architectural and engineering firms to develop design proposals. The stage output in the form of a project brief outlines the key project outputs including design quality aspirations, agreed budget, project delivery programme, and project execution plan.
The next stage is the development of architectural design concepts based on the project brief developed at the second stage. The project design team comprising of architects and engineers produces architectural design concepts integrating strategic engineering and statutory design requirements. The design concepts must also align with the project budget and the strategic quality and spatial aspirations established as part of the project brief. Subsequently, the design concepts are reviewed with the client and project stakeholders to establish and agree the design elements that deviates from the project brief. The stage outputs include agreed architectural design concepts and schedule of derogations, agreed revised project delivery programme and budget.
The fourth stage involves the development of architectural and engineering information including spatial coordination. The key activities at this stage are design development and reviews including engineering analysis, with corresponding project cost evaluations to result in spatially coordinated designs which meets the project budget, quality standards, and delivery programme. Planning application for the delivery of the project is usually submitted at this stage. Also depending on the chosen procurement route, the client may enter into a pre-construction services agreement with a building contractor, where a two-stage procurement approach is applied.
The fifth stage termed technical design, involves further development of the spatial coordinated designs for the construction of the project. The design development at this stage comprises architectural and engineering technical designs and integration of specialist building services design information. Project procurement in the form of preparation and issue of invitation for tender to appoint a building contractor is undertaken at this stage. There is also submission of design information for building regulations application, discharge of reserved pre-commencement planning conditions, preparation of construction phase plan, and submission of F-10 to the Health and Safety Executive, in line with the requirements of the Construction (Design and Management) Regulations 2015.
The next stage termed manufacturing and construction is where the actual site construction activities take place. The core tasks at this stage include finalisation of site logistics arrangement, manufacturing and construction of the building system, monitoring of the site works against the project quality standards and programme, installation and commission of specialist building systems, compliance and discharge of reserved building regulations and planning conditions, compliance of the Construction (Design and Management) Regulations 2015 including the maintenance of appropriate construction health and safety plan, collation of operational and maintenance manual for submission at the project handover.
The seventh stage is when the site construction works are completed, and the project is handed over to the client. The handover activities include inspection and rectification of any defect, submission of project operational and maintenance manual, establishment of aftercare defect management system, and review of project performance.
The last stage of the RIBA Plan of Works is the use of the completed project, which commences after the handover stage. This involves the implementation of facilities and asset management systems. There is also post-occupation review of the building performance against the project quality standards.
Table 2.1 is a systems' analysis of the construction delivery process using the RIBA Plan of Work 2020 stages, as outlined above. Each stage receives input in the form of the output of the preceding stage and the superior main system's environment. This is then processed through the interactions of the human and material resources within the stage, to produce output for the succeeding stage.
2.5 The Construction Project Management System; Differentiation and Risk
The construction project management system is responsible for integrating the different specialist roles involved in project delivery. It derives input from theoretical concepts developed through empirical and analytical studies of the industry performance, plus best practice operational principles. The transformational phase entails the application of management processes including planning, organisation, production, marketing, risk management, and control of the tasks and processes at the different RIBA work plan stages. Figure 2.3 presents a hypothetical illustration of the construction project management system involved in the delivery of a residential development.
2.5.1 Systems Differentiation
The conceptualisation of the construction project management system is linked to the impact of systems decomposition and differentiation (see Figure 2.4). Drawing from the previous theoretical review on systems decomposition (see Section 2.3.3), we can analyse the construction delivery phases and processes as subsystems with different objectives. The principles of general system theory suggest that the different parts of a subsystem will display shared identity in functionality and purpose, which will be different from the micro-objectives of the internal components of the other subsystems within the main system (Bertalanffy 1968, 2015; Blanchard and Fabrycky 1998). Therefore, the more subsystems a system has, the greater the number of different interconnected micro identities will be exhibited, leading to systems differentiation.
According to Walker (2015), differentiation in the construction industry manifests along the lines of the differences in intellectual and emotional orientation among the specialist contributors to a project. It arises from the impact of complex environmental uncertainties, which causes systems components to subdivide into additional specialist groups, to ensure their survival against emerging environmental threats, or take advantage of new potentials created by environmental forces.
The micro-differences within the various construction specialist roles result in differences in how they interpret and respond to changes within the construction environment. The ensuing multiple divergent responses if left unresolved, usually leads to cross-purpose working practices and conflicts, which subsequently affects the project delivery process (Arthur and Pryke 2013). The construction project management system therefore exists to identify and integrate these micro-differences to facilitate collaborative working practices.
Table 2.1 Construction delivery system.
Source: Adapted from RIBA (2020).
RIBA Plan of Work 2020
Input
Transformation
Output
0 – Strategic definition
Client organisation's mission and vision statements
Preparation of business case to guide the appraisal of alternative development options
Preparation of outline client requirements
1 – Preparation and briefing
Outline client requirements
Feasibility studies of the favourable delivery option
Project brief
2 – Concept design
Project brief
Production of architectural design concepts integrating strategic engineering, and statutory design requirements
Architectural design concepts
3 – Spatial coordination
Architectural design concepts
Design development and reviews including engineering analysis, with corresponding project cost evaluations to result in spatially coordinated designs which meets the project budget, quality standards and delivery programme; planning application
