Using Game Theory to Improve Safety within Chemical Industrial Parks

129 Pages·2013·3.234 MB·English

by  Genserik Reniers, Yulia Pavlova (auth.)

Springer Series in Reliability Engineering
Genserik Reniers
Yulia Pavlova
Using Game Theory
to Improve Safety
within Chemical
Industrial Parks
Springer Series in Reliability Engineering
Series Editor
Hoang Pham
For furthervolumes:
http://www.springer.com/series/6917
Genserik Reniers Yulia Pavlova
•
Using Game Theory
to Improve Safety
within Chemical
Industrial Parks
123
GenserikReniers YuliaPavlova
Antwerp Research Group Economic Research Unit
Universityof Antwerp MTTAgrifood Research Finland
Antwerp Helsinki
Belgium Finland
ISSN 1614-7839
ISBN 978-1-4471-5051-0 ISBN 978-1-4471-5052-7 (eBook)
DOI 10.1007/978-1-4471-5052-7
SpringerLondonHeidelbergNewYorkDordrecht
LibraryofCongressControlNumber:2013933592
(cid:2)Springer-VerlagLondon2013
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Preface
Game theory is more than a mathematical gadget for the chemical industry
The chemical industry covers several industrial sectors, including production of
chemicals and the pharmaceutical industry but also the industries manufacturing,
e.g.,paints,varnishes,soaps,detergents,etc.Thecommonelementinthesesectors
is the handling of chemicals on an industrial scale. Companies storing and
transporting hazardous chemicals may also be considered part of this industry.
In the chemical industry, economies of scope, environmental factors, social
motives, and legal requirements often force companies to physically ‘cluster’.
Therefore,chemicalplantsaremostoftenlocatedingroupsinso-called‘chemical
industrialparks’or‘chemicalclusters’andarerarelylocatedseparately.AsFortis
andMaggioni(Curzio2002)state,firmsdecidetosettleinaclusteronthebasisof
the expected profitability of being located there. This profitability depends on
geographicalandagglomerationbenefits,obtainedasthedifferencebetweengross
location-related benefits and costs. As the number of corporations located in an
industrial cluster increases, gross benefits increase due to productive specializa-
tion, scientific, technical and economic spillovers, reduction in both transport and
transaction costs, increases in the quality of the local pool of skilled labor force,
etc.Tomaximizetheclusteringgrossbenefits,chemicalorganizationshavealong
tradition of collaborating on many different fronts. Their cooperative strategies
offer significant advantages for plants that are lacking in particular competencies
or resources to secure these through links with other firms possessing comple-
mentary skills or assets. They also offer opportunities for mutual synergy and
learning (Reniers and Amyotte 2012). Hence, all over the world, chemical
industrial parks bringing physically together a variety of individual chemical
plants, are present.
In the case of chemical enterprises, clustering not only implies profit oppor-
tunities and economic benefits of scale. A chemical cluster has a very high
responsibility toward maintaining safety standards in the urban surroundings as
well. Each additional chemical plant entering a chemical cluster might decrease
the average safety standing of the area.
Companies in chemical clusters are thus not merely linked via technological
spillovers, logistics advantages, service agreements, and so on. They are related
v
vi Preface
through the responsibility of gaining and sustaining safety standards in the entire
industrialparkaswell.However,safetymattersareoftensubjecttoahighdegree
ofconfidentiality.Therefore,safetycooperationstrategiesaredifficulttoestablish.
Nonetheless, since clustered chemical corporations are bonded by the responsi-
bility to keep the industrial area as a whole as safe as possible, individual plants
situated next to one another should develop a safety cooperation strategy.
Insummary,strategicmulti-organizationalcollaborationcanleadtosignificant
advantages in chemical industrial clusters, also—and especially—in the field of
safety.Determininghowbesttoenhancecollaborationbetweendifferentchemical
companies to ensure industrial cluster safety, is thus a topic of great concern.
Furthermore, it is natural to turn to game theory as a mathematical tool for ideas
and approaches to help optimize collaborative situations within a multi-decision
maker context (such as a chemical cluster).
The focus of game theory is interdependence, situations in which an entire
groupofdecisionmakers(e.g.,aclusterofplants)isaffectedbythechoicesmade
byeveryindividualdecisionmakerwithinthatgroup(e.g.,anindividualchemical
plant). In such an interlinked situation, the interesting questions include for
example,whatwilleachindividualdecisionmakerguessabouttheothers’choices,
what action will each decision maker take, what is the outcome of these actions,
and how can the outcome be optimized, does it make a difference if there is a
supra-plant body to give direction to individual decisions, in what way can deci-
sions be influenced, etc.
This book therefore presents the main ideas of game theory and how it can be
employedwithinchemicalindustrialparkstoenhancesafetycooperationbetween
thechemicalplantsbelongingtoacluster.Nospecificmathematicalknowledgeis
neededtounderstandthetheoryexpoundedinthisbook.Nonetheless,allconcepts
are defined precisely, and logical reasoning is used throughout. We are further-
more convinced that the only way to appreciate the theory is to see it in action.
Therefore,weincludedpracticalandillustrativeexamplesthroughoutthedifferent
chapters. The reader will clearly notice that the use of game theory in a chemical
industrialparktoincreasesafety,isverypromising.Gametheoryisthusmorethan
merely a mathematical gadget for the chemical industry.
References
Curzio AQ (2002) Dynamics and models in theory and practice. Physica-Verlag,
Heidelberg
ReniersGLL,AmyotteP(2012)Preventioninthechemicalandprocessindustries:
future directions. J Loss Prev Process Ind 25:227–231
Contents
1 Introduction: Why a Book on Game Theory for Safety
Within the Chemical Industry? . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Objectives and Prospective Readership. . . . . . . . . . . . . . . . . . . 1
1.2 Chemical Industrial Parks. . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.1 Different Levels for Managing Safety Within a
Chemical Industrial Area. . . . . . . . . . . . . . . . . . . . . . . 3
1.2.2 Multi-Plant Safety Background: The Existence
of External Domino Effects . . . . . . . . . . . . . . . . . . . . . 5
1.3 Safety Versus Security: A Brief Description. . . . . . . . . . . . . . . 8
1.4 Game Theory Applied in Safety Management:
Concise Literature Overview. . . . . . . . . . . . . . . . . . . . . . . . . . 9
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2 Safety Management in Chemical Industrial Clusters:
The State of the Art. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.1 Different Types of Accidents Within a Chemical
Industrial Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2 Safety Management in Chemical Clusters: State-of-the-Art
Research and Insights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.3 Safety Management in Chemical Clusters: Shaping the Future
by Using Game Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.4 Effective Collaboration-Induced Cross-Plant Safety
Management. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.4.1 Multi-Plant Safety Culture and Climate. . . . . . . . . . . . . 23
2.4.2 Framework for Dealing with All Types of Accidents . . . 28
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3 Introduction into Strategic Decision-Making. . . . . . . . . . . . . . . . . 35
3.1 Preliminaries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.2 Game-Theoretic Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.3 Strategic Form Games with a Discrete Set of Strategies. . . . . . . 39
vii
viii Contents
3.4 Extensive Form Games with a Discrete Set of Strategies . . . . . . 47
3.4.1 Extensive Games with Perfect Information. . . . . . . . . . . 47
3.4.2 Backward Induction and Subgame
Perfect Equilibrium. . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.5 Hierarchical Tree-Like Games and Imperfect Information . . . . . 52
3.6 Games with Incomplete Information . . . . . . . . . . . . . . . . . . . . 53
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
4 A Game-Theoretic Model for Cross-Plant Prevention
in a Chemical Industrial Park . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
4.1 Introduction: The Domino Effect Game Model. . . . . . . . . . . . . 57
4.2 Coordination Games of Two Players in Application
to the Chemical Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
4.3 Welfare Effect. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4.4 Bayesian Coordination Games. . . . . . . . . . . . . . . . . . . . . . . . . 64
Reference. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
5 An Algorithm to Enhance Safety Collaboration
Within Chemical Industrial Parks . . . . . . . . . . . . . . . . . . . . . . . . 73
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
5.2 The Domino Effects Game Model Revisited: N-Person
Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
5.3 The ‘Tipping Inducing Sub-Cluster’ Concept . . . . . . . . . . . . . . 76
5.4 The TISC Concept Applied to a Cluster Composed
of Three Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
5.5 Searching the TISC for Chemical Clusters Composed
of 3 Chemical Plants or More. . . . . . . . . . . . . . . . . . . . . . . . . 81
5.5.1 Two-Stage Sequential-Move Game of Domino
Effect Prevention . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
5.5.2 TISC-Algorithm and Roadmap for Safety
Cooperation Enhancement Within Chemical
Industrial Clusters. . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
5.6 Stimulating Safety Collaboration in a Chemical Industrial Park:
An Illustrative Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
6 Cooperative Incentives Approach in Case of an MPC
with Limited Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
6.2 The Cooperative Incentives Approach . . . . . . . . . . . . . . . . . . . 92
6.3 Applying the CIA Approach: An Illustrative Example. . . . . . . . 96
6.3.1 Illustrative Example/Situation (1) . . . . . . . . . . . . . . . . . 96
6.3.2 Illustrative Example/Situation (2) . . . . . . . . . . . . . . . . . 99
Contents ix
6.3.3 Illustrative Example/Situation (3) . . . . . . . . . . . . . . . . . 103
6.3.4 Illustrative Example/Situation (4) . . . . . . . . . . . . . . . . . 106
6.4 Discussion of the CIA Approach. . . . . . . . . . . . . . . . . . . . . . . 109
6.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
7 Management Roadmap to Enhance Safety Collaboration
in Chemical Industrial Parks . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
7.2 From Individual Plant Safety Information to Multi-Plant
Safety Information. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
7.3 Toward a Design Code of Good Practice for Enhancing
Safety Collaboration Within a Chemical Industrial Park. . . . . . . 113
7.4 Planning for Safety Sustainability . . . . . . . . . . . . . . . . . . . . . . 117
7.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
8 Conclusions and Recommendations. . . . . . . . . . . . . . . . . . . . . . . . 119
Abbreviations
ALARA As Low As Reasonably Achievable
BNE Bayesian Nash Equilibrium
CEO Chief Executive Officer
CIA Cooperative Incentives Approach
D Down
DPA Delta Process Academy
EFQM European Federation for Quality Management
ERM Enterprise Risk Management
HSE Health, Safety, and Environment
I Invest
IDEAL Improvement Diamond for Excellence Achievement and Leadership
in Safety and Security-model
ISN Industrial Symbiosis Networks
ISO International Standardization Organization
KM Knowledge Management
L Left
MPC Multi-Plant Council
M-PSMS Multi-Plant Safety Management System
NAT Normal Accident Theory
NE Nash Equilibrium
NI Not Invest
OHSAS Occupational Health & Safety Assessment Series
ORDER Optimizing the Risk Decision and Expertise Rad-model
P2T People, Procedures, Technology model
PD Prisoner’s Dilemma game
PDCA Plan, Do, Check, Act-model
PDRC risk Policy, Decision making, Risk, organization Culture-model
R Right
RM Risk Management
SH Stag Hunt game
SMS Safety Management System
TISC Tipping Inducing Sub-Cluster
U Up
xi