vulnerability of human organizations: models and strategies vulnerabilita delle organizzazioni...

Vulnerability of Human Organizations: Models and Strategies

Vulnerabilita delle Organizzazioni Umane: Modelli e Strategie

Adam Maria Gadomskihttp://erg4146.casaccia.enea.it

Information Response

Decision-Making

Managerial IPK and its roles

14 Octobre 2005

An Introduction

Road-map

• Objective of the work• SoA: Human-Organizations Vulnerability

(HOV)• Human-Organization Theory (HOT) • HOT’s Top-Ontology• Social and Cognitive Factors• Critical Relations• IPK, UMP and Role frameworks• Pathologies and Errors• Organization Decision-Making• Strategies• Intelligent Infrastructure Network• Conclusions

The research is focused on:

elaboration of models for the enabling of computer simulation for:

• prediction of events,

• early diagnosis,

• improvement and reinforcement (support)

related to h-organizations’ D-M (Decision-Making).

Vulnerability of h-organization Vulnerability of D-M processes

Early recognition of vulnerability and, in consequence, computer-based decisional support should lead to the reduction/elimination of the possibility of losses caused by various vulnerability of human organizations in situation of emergency, crisis, hazards, …

Objective of the workObjective of the work

[FEMA]

A Vulnerability Analysis allows you to consider many different types of events, which could have a negative impact on your people and your business.

The key to the use of the Vulnerability Analysis is the recognition of the many types of emergencies, which could affect you, and the resources that are available to respond to the emergency.

The State of the art

-There are rich literature about theory of organization and management science

but only few related to Human-Organizations Vulnerability - numerous articles related to specific cases on the Web but without any theory.

- Google: 7 per "human organizational errors".

- Google: 449 per human, "organizational vulnerability".

- Google: 549 per "BUSINESS vulnerability", organization.

-"human organizational vulnerability", - non ha prodotto risultati in nessun documento.

-"human organization vulnerability", - non ha prodotto risultati in nessun documento.

-The domain is relatively new but it grows very fast.

SoA: Human-Organizations Vulnerability (HOV)SoA: Human-Organizations Vulnerability (HOV)

The State of the Art in the HOV modeling

Three main types of modeling approaches in the SoA:

1. Soft modeling: descriptive, partial and intuitive – human-oriented

2. Hard mathematico-physical modeling: partial, continuous processes, difficulty with measurements, idealistic – for illustrative simulations, external observer. Computer oriented.

3. Flexible socio-cognitive modeling: computational, real-world, systemic, AI techn., external and internal observers. For simulation and decision-support. Human-computer oriented. In the development.


Intuitive Problem identification

Vulnerability: Lack of immunity or insufficient résistance on unexpected events.

Two basic types of vulnerability:

A.Vulnerability on external events: dangerous situations, attacks, intrusions

B. Vulnerability on internal events: internal crisis, pathologies, reorganization.

Some observations

- Attacks, intrusions are intended to destroy key functionalities of the organisation while fraud is designed to make money for the perpetrator [John.Bigham,2004]

Most danger are attacks from within the organisation, viz. from disaffected employees and the software they use, or people obtaining passwords through organization

employers.

A recent survey in USA has shown that around 30-40% of attacks have their sources within the enterprise.


Some observations

A recent survey in USA has shown that around 30-40% of attacks have their sources within the enterprise.

Therefore this attacks are most efficient and dangerous. They are human dependent and their analysis have to involve sophisticated socio-cognitive models.

B type vulnerability Hannan and Freeman (1984) developed a (soft) theory of structural inertia withtwo main parts. The first part claims that social selection processes favor organizational inertia. The core insight is that social actors have the unintended resistant to change.According to them, two situations generate loose coupling: - diversity of interest among members and- uncertainty about means-end connection.It means that organizations respond relatively slowly to threats and opportunities in the environments. If it takes less time to build new organizations that fit a new environment than to reorganized existing

organizations.


Some examples:

Hard Mathematical model of survival analysis of human organization (Cox and Oakes 1982).

Hazard related to the dead of a human organization during reorganization changes. t

Haz(x, s, t) = haz (x, u)du sx – organization indicators - moment of the official decision of an reorganization t - moment of the end of reorganization

In this case, the probability of the resistance of the reorganization in moment t is (1- G(x, s, t)), where: tG(x, s, t) = Pr {surv(x, s, t) = 1} = exp haz (x, u)du = exp(Haz(x, s, t))

s 1 if u [u [s, t) → risk(x, u) = 1],∀ ∈surv (x, s, t) = 0 otherwise.

Here, a risk is defined as a binary function risk(x, s) mapping from organizations and time points that equals 1 if x is at risk of mortality (and, therefore, has not yet experienced mortality) at s and equals 0 otherwise.

Unfortunately such fundamental function as haz (x, u) is not defined by the authors.


Some recent examples: Recent studies, Complexity, Science and Society Conference, 2005, Crisis Response Systemsthrough a Complexity Science Lens, A. Paraskevas ,Oxford Brookes University

Crisis Management is increasingly gaining importance in organizational literaturedue to the precipitous growth in the total number of organizational crises over the past 4years. The practices currently employed are largely based on a linear command-and-control management approach aiming at very specific results.Managers increasingly realise “…that anytime you are not in a crisis,you are instead in a pre-crisis mode” (Fink, 1986:5).

Complexity perspective ( in preliminaty phase): Self-awareness by Diffuse FeedbackIn the absence of central control, the crisis response system must to monitor its overall performance. Segel (2000).

Summarising, numerous studies lead to the conclusion that a main critical aspect of vulnerabilities of human organization is a decision-making.


HOT is a subtheory of TOGA

HOT is a Real-World theory, it means it has to be complete on the level of generality of a real-world description in order to fulfill utility requirements.

Remark: Every theory is a knowledge.

Most general,

let U denotes an infinite set of the real world states, and Mx denotes a complete model of U then Thy is a real world theory if

Human-Organization Theory (HOT)Human-Organization Theory (HOT)

Thy(U) Mx

Examples of a complete description of the U

M1: { A, B }, where A are all material objects and B are all only energy objects.

M2: {A, B, C, D }, where A are all humans, B are all their interactions, C are other

U components, D are other interactions.

Methodological soc-cog framework: TOGA

According to the current needs. TOGA will be introduced successively and we will use TOGA’s:

- axioms…

- terminology

- generic systemic computational models

- methodology

Top-down – problem recognition & specification

Object-based – a fundamental conceptualization

Goal-oriented – problem recognition & specification

Approach

Remark: Computationability requires a mathematical formalization.

HOT’s Top-Ontology: First comprehension levelHOT’s Top-Ontology: First comprehension level

Human organization,

Environment,

Interactions, R

(, R, )

Foundation Goal,

Human organization is an artificial system which includes human components

R

(, .)

(.) ?

We use: G-S interrelation

Theorem

Every components of the triple (, R, ) is

decomposable, i.e. 1, 2, … R1, … 1, 2, … are

functionally, processually and structurally connected.

i, Rj, k which are components subsequently of : , R, .

A modeler ( M ) perspective

M

Valid for every problem

HOTHOT Top-Ontology: Definition of vulnerabilityTop-Ontology: Definition of vulnerability

Human organization,

Environment,

Interactions, R

Domain of Activity,

States, S

Foundation Goal, …

Vulnerability on X , v

Vulnerability v(, X) is an attribute of , when exist such class of S(, )

which produces losses for in the case of the R| X , where X denotes a specific

class of R charactized by a risk.

Possible h-organization worlds

include domains of activity with:

- goal-domain

- cooperation domain

- intervention domain.

Abstract objects

HOTHOT Top-Ontology: Identification of vulnerability:Top-Ontology: Identification of vulnerability:

Human organization,

Environment,

Interactions, R

Domain of Activity,

States, S


Vulnerability on X , vRisk r

Observation time

Interval T

Identification of the vulnerability requires an identification of

objects and relations involved:

v(, X) W (, , S(, ), R|X )

W - denotes a world of problem.

On the other hand, identification of v(, X) is necessary for its analyzing and reducing.

Therefore we need to have a problem-independent framework of a generic world of problem :

W (, , S(, ), R|X (r, .), T)

Such model has to be decomposed successively and should enable to observe and simulate pathologies of organizations which lead to organizational erroneous decisions.

HOTHOT Top-Ontology: Identification of Problem WorldTop-Ontology: Identification of Problem World

W (, , S(, ), R|X (r, .)) ……… (*)

is a carrier of organizational decisional processes (ODM).

ODM is constructed on different levels of h-organization.

We need to identify such set of observable/measured

attributes (AW) which will be common for the model of W and ODM.

In this case, modification of ODM will change W and will

lead to the changes of v(, X).

In order to find AW the components of the W model (*) have to be decomposed and individually modeled.

Some separate models of the W-model components are in the subject matter literature.

Human organization,

Environment,

Interactions, R

Domain of Activity,

States, S



Observation time

Interval T

Problem world W

Decisional ODM processes

Common Space AW

HOTHOT Top-Ontology: Models ofTop-Ontology: Models of thethe components ofcomponents of WW-model -model

We have many specific models of:

• organizations,

• their domains of activity,

• risky and losses generation events (emergency, crisis, …)

• managerial decisional mechanisms,

but they have numerous different goals, conceptualizations (ontologies), and are not integrated/ordered for the vulnerability modeling.

Anyway some critical relations between W-models components are recognized.

Human organization,

Environment,

Interactions, R

Domain of Activity,

States, S



Observation time

Interval T

Problem world W

Decisional ODM processes

Common Space AW

The main are:

ODM – organization structure Individual risk – organization risks – ODM Event types - ODM constrains

Social Factors: Decomposition of the DomainSocial Factors: Decomposition of the Domain

Social factors identification

They require decomposition of the organization environment.

1

2

n

Organization World: decomposed objects and relations

intervention

cooperation

dependence

m

Social factors:

a. development/lifecycle phase; new, old …

b. structural constrains

c. preparedness : proper exercitations

d. politic influences

e. technological communication

infrastructures

Cognitive Factors: Decomposition of an OrganizationCognitive Factors: Decomposition of an Organization

Cognitive organizational factorsi. individual motivations

ii. accepted risk

iii. individual power and autonomy

iv. individual recognition

Organizational unit

human unit

technological support unit

Critical relations:

ODM (decision-making) – org.structure

Critical relations: decision-making – org.structure

EXAMPLES:

1. CASE STUDYThe Collapse of Decision Making and Organizational Structure on Storm King Mountain, T. Putnam, Ph.D. USDA Forest Service, Missoula Technology and Development Center,1995.

2. SOFT MODEL: Restrictive Control and Information Pathologies in

Organizations, W. Scholl Journal of Social Issues, Vol.55 Issue 1, Spring 1999 :

Restrictive control is a form of power exertion in which one actor pushes

his wishes through against the interests of another actor. In contrast, if an actor influences the other in line with his or her interests, this is called promotive control. … (common interests).Restrictive control has negative consequences for the production of new or better knowledge, because it induces information pathologies that in

turn lower the effectiveness of joint action. These two hypotheses are tested in a study on 21 successful and 21 unsuccessful innovations.

Critical relations: intelligent object - decision-making

Organization is seen as an embedded intelligent complex object: new cognitive, AI, socio-cognitive perspectives are involved.

From last 15 years Studies are focused on numerous specific cases:

artificial societies, emotions, cognitive decision-making. An illustration:

- International Workshops: Engineering Societies in the Agents World,

- Periodical Workshops: "Emotion-Based Agent Architectures"

- Emotions in Humans and Artifacts, MIT Press , 2003

- Journal of Artificial Societies and Social Simulation.

- Workshops: Modelling Artificial Societies and Hybrid Organizations

- Google: 2.850.000 per high-risk, decision-making

- Google: 5.620.000 per cognitive decision-making, Systemic Approach

IPK : TOGA Intelligent Agent Decomposition Paradigms

Information is processed by Knowledge: I’ = K j( I ), j=1, …N, for l

where choice of j depends on Preferences.

- Information -

- How situation looks - Past/Present/Future states of Domain-of-Activity (D-o-A)

- Preferences - - A partial ordering of possible states of D-o-A and they determine what is more important

- Knowledge - - What agent is able to associate (descriptive/model knowledge: rules, models) - What agent is able to do in Domain-of- Activity (operational knowledge)

I

KP

“ Mind Cell” Elementary IPK Computational

Model

IPK Cognitive Architecture

Copyright High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it Adam M. Gadomski, 23/06/2005

Intell. Object Modelling

http://erg4146.casaccia.enea.it/

IPK Cognitive ArchitectureIPK Cognitive Architecture



IPK: Cooperative Intelligent Objects

Real EmergencyDomain

Agent 1

Agent 2

Agent 3

Agent N

I2

PK

In

P C

I1

P

K

I3

P

K

Infrastructure Network

. . . .I – information system

P – preferences system

K – knowledge system

Agent Manager

I

P

K

Example

Copy rights High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it Adam M. Gadomski, 8/10/2003

[Balducelli,Gadomski,1993]


IPK Bases: an example



Component Errors Modelling


Human ERRORs: Not proper or not sufficient Information

Lack or not proper Importance Scale (Preferences, risk ass.)

Not proper or not sufficient instructions, procedures (Knowledge)

Wrong Cognitive and Organizational Factors (Motivations).

Models are Knowledge

Problem Specifications are: Requested & Modified

Information

Motivations create proper Preferences which activate adequate Knowledge

Basic Modelling Framework

IPK Cognitive computational model (Information, Preferences, Knowledge) Application

I

KP

I2 = Ki I1, where Ki = P {K}


SOCIO-COGNITIVE ENGINEERING: an Intelligent Organization


TOGA theory framework

OrganizationMission/Fundation-Goal Products/Actions

General Functional Frame

Intelligent Organization is specified by:

set of roles,

structure,

decisional mechanisms, ODM , and

Resources/means, , such as information network

(, , ODM, )

All of them can be a cause of

Vulnerability: v(, X) .

Unexpected events


Fig. 1. H-Organization: A graphical illustration of Universal Management Paradigm (UMP): the cooperating-manager environment from the subjective perspective of a pre-

selected decision-making manager [4].

DOMAIN OF ACTIVITY AND MANAGER’s GOAL-DOMAIN

EXECUTOR

information tasks

ADVISOR

expertises COOPERATINGMANAGER

cooperation

SUPERVISOR/ COORDINATOR

tasksinformation

Knowledge & Preferences repository

INFORMER

MANAGERMANAGER

with the same relative internal structure

UMP includes 6 canonical roles and their interrelations

Components: Universal Management Paradigm (UMP)Components: Universal Management Paradigm (UMP)

Dynamic Role Model (computational)

Definitions according TOGA

Role (competences, duties, privileges )

Competences: what he/she/it is able to do, possessed models of the domain (knowledge)

Duties: responsibility, tasks and requested preferences

Privileges: Access to the information. It produces conceptual images of the domain. Access to execution tools (information); org.power.

The roles are specified by their own IPK Bases Set:

Information Bases – how situation looks, continuously updated

Preferences Bases – importance scales/relations, ethics rules

Knowledge Bases – required models & know how


Remark: Structure depends on roles, and roles depend on IPKs


Pathologies of Organizations: Examples

Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/

High-Intelligence & Decision Research Group, 2005

HID

Complex situation: Every human-agent is in 3 roles together :

1. Organizational role – requested/defined by the structure (fixed)

2. Informal role – applied, structure independent (variable)

3. Personal/real role – really realized (variable)

Conflicts of Roles

Compromise, inefficient risky decisions. Necessity of negotiations

Dynamics of roles may create different lack of congruence between them & conflict of interests

Conflict of Interests/Motivations

Differ Risk-Benefits relations for

All of them influence ODM

Social interest

Organization interest

Personal interest

Decision-Making


New Information or task

Knowledge Base

Preferences Base

Decision-Making

No action/response

Meta-action/Pseudo-action

Action adequate to D-M’er role and situation

Cognitive Definitions [TOGA]

Decision-making: an individual or group reasoning implied by the request/necessity of a choice caused by received information or task, or by delivered conclusion about possibility of risks/benefits. It is started when either choice criteria are unknown or alternatives are unknown and finished when choice is performed.

Action-oriented decision-making: it is a decisional process when alternatives represent possible actions in pre-chosen physical domain.

Mental decision-making: when the final choice refers not to actions but to conceptual objects related to a preselected domain of activity of intelligent agent.

Group decision-making: when responsibility for decision is allocated to a group of intelligent agents and is based on shared decision-making process.


Pathologies of Decision-Making (computational models)


Controlability & updating of Ethics concept

reasoning pathcriticalnode

alternatives

d-mdata decision

??

??

decision

Types of Proper and Pathological Decisions

Main classes: - meta-D-M , - pseudo D-M, - proper D-M.

Pathologies are related to:

- response on source type ( “safety” filters );

- response on subject ( lack of competences, emotional reaction, out of Interest).

- response according domain-preferences (organizational/personal role): proper DM.

If D-M autonomy increases then: Efficacy of Control decreases & Importance of Ethics and personal motivation increases. This rule indicate importance of Motivation Management.


Pathology of Bureaucracy: two iron lawsPathology of Bureaucracy: two iron laws

There are two iron laws of bureaucratic behavior of the self-aggrandizement managers :

1. They tend to maximize the resources they control, usually at the expense of their competitors within the organization.[J. Wilson, 2005]

2. They (in different manners) tend to minimaize their own personal risk. [G.Ridman, 2001]

The primary: such actions increase subjective security and informal power.

The second law implies that managers tends to take only unavoidable risks, and all decisions that seem to carry some risk to the decision-maker will be (bucked up) as far as possible.

These laws apply equally to private- and public-sector.

Frequently the personal risk is hidden and officially “does not exist” but it influences strongly bureaucratic decision-making, and it is significant component of vulnerability (VoHO).

Strategies: continuous improvementby D. Keith Denton, Creating a system for continuous improvement - improving an

organization's decision-making process. Business Horizons, Jan-Feb, 1995

• To have continuous improvement , there has to be some factor that binds people together.

• There must be a common purpose, and each member must understand his or her role.

• If you want real, long-lasting change, then you must have a way of focusing people on the change.

Individual motivation building is essential factor for the organization continuous improvement and robustness.

Strategies: Human-OrientedStrategies: Human-Oriented MANAGEMENT OF STRATEGIES:

A primary concern of every consumer of management theory is to understand where it applies, and where it does not apply. {Paul R. Carlile, 2005]

On November 14, 2005, KMCI will hold its One-Day Workshop on Reducing Risk by Killing Your Worst Ideas.

Most contemporary approaches to risk concentrate on assessing risk in the context of some model being applied by the person or group assessing risk, so if that model is false or illegitimate the risk assessment is too.

This workshop views risk assessment from this internal perspective.

It tells you how to reduce risk, particularly in business, by using both creative learning

and critical thinking. The problem of a wrong strategy choice how to cope with vulnerability

- What is clear but How is not yet well defined.Systemic Approach

Response STRATEGIES: TOGA

Strategy ( A, B, C, D, E, F , . ) is a pattern for a class of actions, it depends on attributes of , and R|X..

Components of a Strategy in different phases of the lifecycle of an organization ( they have decrease vulnerability v(, X) ).

A. Learning (continuous knowledge acquisition)

B. Training (real, simulated), games

C. Motivation building (individual, group), competition

D. IDSS functions (computerized, real-time)

E. Reorganization (in crisis)

F. Bottom-up local reasoning according to clear and accepted top-down rules (routine).

Strategies: Intelligent Infrastructures (IIN)Strategies: Intelligent Infrastructures (IIN)

IINs are highly autonomous systems which support services and industrial/production systems enabling them to execute human end-users oriented functions.

IINs are one of emergent challengers of our new century, they are feasible for realization.

Recently, intelligent infrastructures networks or intelligent networked infrastructures( a "multi-brain nervous system") are becoming emergent components of embedded dependable computer and human-computer systems.

They should lead to the building of different forms of "collective intelligence“ (organiz-human-computer).


EC, Unit G3: "Embedded Systems"


Abstract Intelligent Kernel for Intelligent Infrastructures

Functional requests

We need a software module with capacity of: - autonomy in decision making - reasoning/inferencing in problem solving - learning from the environment and from communication - modification of its own goal - modeling/identification of its world (discovery) - knowledge and information acquisition by communication - interaction with environment by effectors and communication. ... and TOGA includes a preliminary framework of such abstract properties.



Applications: TOGA Methodology for Intelligent Kernel Design

From the ENEA’s Tech. Proposals of the EU Project EIDA,1996 & EMIR 2004

(Abstract Managerial Intelligence)

Based on SPG Approach.

Infrastructure Simulation Game System

World Editor

World Simulator

IntelI.Infrast.Kernel

Human Supervisor or Manager

“Absolute Observer” (designer)

Interface

Servicies Units

Communication

Interface

Communication

Servicies Functional Units Intelligent Infrastructure

Top view of the Infrastructure Simulation Game System



MANAGERMANAGER

INFORMERs EXECUTORs

information tasks

ADVISORs

expertises COOPERATINGMANAGERs

cooperation

SUPERVISOR

tasks informationKnowledge Preferences

An example: Intelligent Chip for m-Learning & m-IDSS

I-Chip

USB m PC PC+Web

Intelligence Infrastrutture Network

Domain of Activity

Artificial Organization – mixed two webs

(Personoids, see Web)http://erg4146.casaccia.enea.it/wwwerg26701/per-hom2.html


TOGA’s-Model


Computer support & substitution of human functions

HUMAN tasks COMPUTER personoids tasks

Life-functions Information Systems & DSSs or Robots

Social-functions (Decision-Making Sypport Systems) Activities

% contribution to an activity/task

100

50

00

trend

Development of autonomous computer infrastructure networks

IIN: Final Remarks “ Mission, Unit G3: "Embedded Systems" (Kostas Glinos)

To be the focal point and integrator for research in embedded systems in Europe. The aim is to strengthen Europe's position in pervasive, networked and dependable embedded systems

by integrating and extending the scientific and technological base, by promoting innovation and top-quality research and by increasing industrial capabilities. “

-----------------------------

Meta-Strategic Thinking ??

New problems dramatically need the reinforcement of the integration of theoretical frameworks with applications.



Some References, 11. A.M. Gadomski .TOGA: A methodological and Conceptual Pattern for modelling of Abstract Intelligent

Agent. In Proc. of the ‘First International Round-Table on Abstract Intelligent Agent’,25-27 Jan 1993, Enea print (1994).

2. A. M. Gadomski. Personoids Organizations: An Approach to Highly Autonomous Software Architectures, “11th International Conference on Mathematical and Computer Modeling and Scientific Computing,, March 31 - April 3, 1997, Georgetown University Conference Center, Washington.

3. A.M.Gadomski et al., Towards Intelligent Decision Support Systems for Emergency Managers: The IDA Approach. International Journal of Risk Assessment and Management, IJRAM, 2001, Vol 2, No 3/4.

4. A. M. Gadomski, Meta-Knowledge Engineering Server (since \997): http://erg4146.casaccia.enea.it

5. Hannan, Michael T., and John Freeman, "Structural Inertia and Organizational Change." American Sociological Review, 49 (1984): 149-164.

6. Amburgey, Terry L., Dawn Kelly, and William P. Barnett, "Resetting the Clock: The Dynamics of Organizational Change and Failure." Administrative Science Quarterly, 38 (1993): 51-73

7. Levinthal, D., "A Survey of Agency Models of Organizations." Journal of Economic Behavior and Organization, 9 (1988): 153-185

8. Eisenhardt, K. M., "Agency Theory: An Assessment and Review." Academy of Management Review, 14 (1989): 57-74.

9. Simon, H. (1976), Administrative Behavior (3rd edition). New York: The Free Press.

10. Allison, G. (1997), The Essence of Decision. Glenview, IL: Scott, Foresman & Co.

© ENEA, 2004. A.M.Gadomski., E-mail: [email protected]

References, 2

Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/

High-Intelligence & Decision Research Group

HID

1. A.M. Gadomski , SOPHOCLES - - EUREKA & MURST & ENEA: Intelligent Cognitive Systems Engineering, Transparent-sheets, 20/09/2000, Updated 17/06/2001 ENEA , ITEA materials.

2. A.M. Gadomski , SOPHOCLES Project – Cyber Virtual Enterprise for Complex Systems Engineering: Cognitive Intelligent Interactions Manager for Advanced e-Design,

Transparent-sheets, 28/08/2001, ENEA. ITEA materials.3. A.M.Gadomski. TOGA: A Methodological and Conceptual Pattern for modeling of Abstract

Intelligent Agent.Proceedings of the "First International Round-Table on Abstract Intelligent Agent". A.M. Gadomski (editor), 25-27 Gen., Rome, 1993, Published by ENEA, Feb.1994.

4. A.M.Gadomski, "The Nature of Intelligent Decision Support Systems". The key paper of the Workshop on "Intelligent Decision Support Systems for Emergency Management ", Halden, 20th-21st October, 1997.

5 . A.M.Gadomski, S. Bologna, G.Di Costanzo, A.Perini, M. Schaerf. Towards Intelligent Decision Support Systems for Emergency Managers: The IDA Approach. International Journal of Risk Assessment and Management, 2001.

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vulnerability of human organizations: models and strategies vulnerabilita delle organizzazioni...

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