redalyc.a theory of organizational cognition: … · organizaÇÕes a theory of organizational...

Revista de Administração FACES Journal

ISSN: 1517-8900

[email protected]

Universidade FUMEC

Brasil

Nobre, Farley Simon; Tobias, Andrew M.; Walker, David S.

A THEORY OF ORGANIZATIONAL COGNITION: PRINCIPLES AND CONCEPTS

Revista de Administração FACES Journal, vol. 7, núm. 4, octubre-diciembre, 2008, pp. 11-30

Universidade FUMEC

Minas Gerais, Brasil

Available in: http://www.redalyc.org/articulo.oa?id=194016900002

How to cite

Complete issue

More information about this article

Journal's homepage in redalyc.org

Scientific Information System

Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal

Non-profit academic project, developed under the open access initiative

http://www.redalyc.org/revista.oa?id=1940

http://www.redalyc.org/articulo.oa?id=194016900002

http://www.redalyc.org/comocitar.oa?id=194016900002

http://www.redalyc.org/fasciculo.oa?id=1940&numero=16900

http://www.redalyc.org/articulo.oa?id=194016900002

http://www.redalyc.org/revista.oa?id=1940

http://www.redalyc.org

FACES R. Adm. · Belo Horizonte · v. 7 · n. 4 · p. 11-30 · out./dez. 200810


ORGANIZAÇÕES

FACES R. Adm. · Belo Horizonte · v. 7 n. 4 · p. 11-30 · out./dez. 2008 1 1

FARLEY SIMON NOBRE · ANDREW M. TOBIAS · DAVID S. WALKER

ORGANIZAÇÕES

A THEORY OF ORGANIZATIONAL COGNITION:PRINCIPLES AND CONCEPTS

A TEORIA DA COGNIÇÃO ORGANIZACIONAL: PRINCÍPIOS E CONCEITOS

Farley Simon NobreThe University of Birmingham

Andrew M. TobiasThe University of Birmingham

David S. WalkerThe University of Birmingham

RESUMO

Organizações e mudanças do ambiente ao longo do tempo. Não é só mudar as suasestruturas e processos de funcionamento, mas também as perspectivas que os investigadorestêm acerca deles por períodos de tempo. Assim, os cientistas precisam fazer uma revisãodas teorias das organizações, a fim de formular novas soluções para os problemas dopresente. É nesse sentido do pensamento que esse trabalho contribui através da introduçãode novos conceitos, princípios e proposições para uma teoria da cognição organizacional. Écolocado novas perspectivas sobre a organização e o ambiente, e também sobre as relaçõesentre eles através do conceito de cognição. A partir dessas origens, esta investigação contribuitambém por apresentar os conceitos de autonomia e inteligência organiza-cional, níveishierárquicos da cognição nos sistemas organizacionais, juntamente com definições cognitivase modelos complexos de organização e do ambiente.

PALAVRAS-CHAVE

Organizações. Ambiente. Cognição. Sistemas complexos. Fuzzy sets.

ABSTRACT

Organizations and the environment change over time. Not only change their structures andprocesses of functioning, but also the perspectives that researchers have about them overperiods of time. Hence, scientists need to review theories of organizations in order to formulatenew solutions to the problems of the present. It is in such a direction of thinking that thispaper contributes by introducing new concepts, principles and propositions towards a theoryof organizational cognition. It put forwards new perspectives about the organization and theenvironment, and also about the relations between them through the concept of cognition.



From these backgrounds, this research also contributes by presenting the concepts oforganizational intelligence and autonomy, hierarchic levels of cognition in organizationalsystems, along with cognitive definitions and complex models for the organization and theenvironment.

KEYWORDS

Organizations. Environment. Cognition. Complex systems. Fuzzy sets.

INTRODUCTION

Principles of organizations evolved with ancientand medieval civilizations, and developed andmatured after the Industrial Revolution in Europein the 18th century and latterly in the United Statesof America in the 19 th century. Such atransformation flourished gradually after the apogeeof the Renaissance and the Enlightenment Agesin Europe which was marked by a period ofrevolution in thinking, supported by religious,economic, social, technological and politicalchanges (WREN, 1987). The gradual maturationof organizations was encompassed bytransformations in the perceptions, behavior andmotives of their participants, developments intechnology, the need for new organizationalprocesses and structures of normative andbehavioral parts, the human desire to pursue morecomplex goals, developments in social sciences,behavioral and cognitive psychology along withgeneral systems theory, changes in theenvironment, and also due to intensive processesof globalization (NOBRE, 2008).

Modern organizations emerged gradually afterthe Industrial Revolution and they were challengedby new political, economic, social and technologicalcontexts. Hence, schools of organizations andmanagement were developed in order to supportthe analysis of the new organization and the designof new organizational structures and processes.Such schools emerged from the first decade ofthe 20th century, giving rise and maturation to thediscipline of organization theory (KHANDWALLA,

1977; MARCH, 1965; SCOTT, 1998). They startedwith theories of bureaucracy, principles of scientificmanagement and administrative theory, and theyreceived new insights from the experiments of thehuman relations school (PUGH, 1997). Theyadvanced with the contributions provided by theschools of administrative behavior and decision-making (MARCH; SIMON, 1958, 1993; SIMON,1947, 1997B), systems theory (SILVERMAN,1970), socio-technical systems (TRIST, 1981),contingency theory (GALBRAITH, 1973, 1977),organization design (GALBRAITH, 2002), economicorganizations (MILGROM; ROBERTS, 1992),computational organizational theory (CARLEY;GASSER, 1999), organizational learning (DIERKESet al., 2003), organizational cognition (NOBRE etal., 2008), among other schools. In such a path,organization theory has reached the 21st centuryas a formal and mature discipline supported bythe rigorous contributions of these schools.

The literature about organization theory has alsoprovided distinct, complementary and commonperspectives on organizations. The publicationsencompass books which cover different writers oforganizations (PUGH; HICKSON, 1997), diversetypes of organizations (MCKINLAY, 1975; MARCH,1965), prominent comparative studies of differentclasses of organizations (BLAU; SCOTT, 1963), andalso references that broadly survey literature results(HODGE et al., 2003; SCOTT, 1998).

These evolutions and diversities of schools oforganizations exist because the organization andthe environment change over time. Not only



change their structure and processes of functioning,but also change the perspectives that researchershave about them over periods of time. Hence,scientists need to review theories of organizationsin order to formulate new solutions to the problemsof the present. It is in such a direction of thinkingthat this paper contributes by proposing newconcepts, principles and propositions towards atheory of organizational cognition. It comprises theselection of diverse perspectives of organizationsand also the unification of them towards a neworganizational theory whose principal element iscognition. Its content is mostly influenced by thecontributions given by the schools of administrativebehavior, decision-making and bounded rationality(MARCH; SIMON, 1993; SIMON, 1997a, 1997b),systems theory (BUCKLEY, 1968; KHANDWALLA,1977), socio-technical systems (TRIST, 1981),contingency theory (GALBRAITH, 1973, 1977),organizational learning and knowledgemanagement (DIERKES et al . , 2003),computational organization theory (CARLEY;GASSER, 1999) and also the perspectives ofrational, natural and open systems (SCOTT, 1998).

Initial lines of contribution as outlined in thispaper to the perspectives of organizationalcognition were first touched in (NOBRE, 2002,2003a, 2003b, 2004a, 2004B). Latterly, theseperspectives were further developed and extendedto new concepts, theories and practices aboutorganizational cognition that subsume cognitivemachines in organizations (NOBRE, 2005, 2008;NOBRE et al. 2008). In these publications, theauthors also presented evidence through empiricalresearch that indicates the alignment of theirpremises and propositions with results of anindustrial case study that also contributed to outlinenew directions to assess, to evaluate and tomeasure the degree of organizational cognition.Therefore, it is from these backgrounds that thispaper presents its contributions. It outlines rationale,concepts, principles and propositions towards atheory of organizational cognition.

From a macro point of view, what makes thispaper distinct is that it put forwards newperspectives about the organization and theenvironment, and also about the relations betweenthem through the concept of cognition. In such aview, organizational cognition is contingent uponthe environment. Moreover, this paper focuses onthe general picture of organizations pursuing highdegrees of cognition in order to reduce the relativelevels of uncertainty and complexity of theenvironment. Therefore, it does not discriminateorganizations by their type and purpose (i.e., profitor non-profit industries, public or private institutions,manufacturing and service firms, unions, armies,schools, and so on); nor by their size; nor by theirgeographical location, east-west; and nor by their age.

From a micro point of view, this researchproposes principles about organizational cognitionand it clearly distinguishes organizational cognitionfrom the concept of organizational learning. Itoutlines the concept of hierarchic levels of cognitionin organizational systems and thus it proposescognition as an important element of theorganization. It presents definitions of organizations,environment along with the relations betweenthem through cognitive perspectives. Suchdefinitions include concepts of intelligence,cognition, autonomy and complexity fororganizations. It derives a definition ofenvironmental complexity and it proceeds byintroducing propositions about the relationsbetween organizational complexity andenvironmental complexity. While the former issynonymous with organizational cognition, thelatter is synonymous with environmentaluncertainty. All these backgrounds together forma theory of organizational cognition and theysupport the perspective of organizations pursuinghigh degrees of cognition.

CRITICAL VIEW AND MOTIVATIONS

Organizational cognition is a discipline whichhas its foundations based on multidisciplinary



research areas that span from social sciences,economics, business administration, management,sociology, political science, anthropology,philosophy, psychology, information systems,cognitive sciences and computer sciences to otherareas that play an important part in organizationalstudies, organizational behavior and organizationaltheory (NOBRE et al., 2008).

The subject of organizational cognition hasbeen touched in the literature after advancementsin the discipline of organizational learning whichhas received important and diverse contributionsfrom distinct researchers (ARGYRIS; SCHON, 1978;MARCH; OLSEN, 1975; SENGE, 1990).

Multidisciplinary studies on organizationallearning and knowledge management arepresented in (DIERKES et al. 2003); and onorganizational intelligence, and organizationsresembling information processing systems anddistributed computational agents are presented in(BLANNING; KING, 1996; CARLEY; GASSER, 1999;PRIETULA et al., 1998). However, a formal studywhich relates organizations with concepts ofcognition and learning (innovation) was previouslyand firstly proposed in (SIMON, 1947; MARCH;SIMON, 1958; SIMON, 1997b).

Nevertheless, despite existing someconnections in between organizational learning,knowledge management, organizationalintelligence and organizational cognition, this lattersubject has began to receive more attention onlyfrom the beginning of the 21st Century, after somebook publications. The edited book by Lant andShapira (2001) for example, presents a collectionof chapters on the subject of cognition and itsimpact on organizational studies. Contributors totheir book chapters include well-known researcherssuch as James March and Willian Starbuck.However, despite providing the literature with aset of chapters that introduce many perspectiveson the general subject of organizational cognition,Lant and Shapira’s book does not give a concisedefinition of organizational cognition. Moreover,

and most important, it does not make a cleardistinction between the concepts of organizationalcognition and organizational learning, knowledgemanagement, among other related terminologieswhich have been used through an interchangeableway in most of the literature on these subjects.Another publication which does not clearlydistinguish these terms is the book of Iandoli andZollo (2007).

Proceeding further, what makes this paperdistinct and unique is that it provides a set ofprinciples, definitions, premises and propositionstowards a theory of organizational cognition. Itclearly derives definitions on organizationalcognition and it also distinguishes organizationalcognition from organizational intelligence,organizational complexity, organizational autonomyand organizational learning. Moreover, it setscognition as an important element of theorganization. From all these backgrounds, thisresearch raises a number of questions in our questfor answers and it opens new directions for futureresearch on organizational cognition, organizationdesign, analyses of cognitive machines inorganizations and also methods to assess, toevaluate and to measure the degree oforganizational cognition (NOBRE et al., 2008).

ORGANIZATIONS

Model of the Organization

Organizations benefit individuals by extendingtheir cognitive, physical, temporal, institutional, andspatial limitations (CARLEY; GASSER, 1999;NOBRE, 2008). They integrate participants,technology and goals into a coordinative socialstructure in order to cope with the environment.Participants are the agents which act in the nameof the organization. Technology expands whatorganizations can do and it supports the connectionof the organization to the environment. Goals andsub-goals are what organizations aim to achievein order to satisfy their desires. Social structure

FACES R. Adm. · Belo Horizonte · v. 7 n. 4 · p. 11-30 · out./dez. 2008 15


Figure 1

A Model of the Organization (Scott, 1998)

Figure 2

Uncertainty as Lack of Information

refers to the standards and regularized aspects ofthe relationships existing among the participantsin the organization; it comprises normative andbehavioral structures (NOBRE, 2008). Theenvironment includes information, consumers andstakeholders, other organizations like buyers andsuppliers, networks of organizations, institutions,market regulators, the whole economy, culturalvalues and natural resources (MILGROM,ROBERTS, 1992; SCOTT, 1998). Figure 1 illustratesa model for the organization. The elements of theorganization are interdependent and the wholeorganization is connected with the environment.

Limitations of Organizations

Contingency theory (GALBRAITH, 1973, 1977)has defined uncertainty as the variable whichmakes the organization contingent upon the envi-ronment. Hence, organization design, and thusorganizational choice, depends on the concept ofuncertainty. Briefly, uncertainty can be associatedwith the mathematical concepts of probability andfuzziness (KLIR; FOLGER, 1988). However, uncer-tainty can also be associated with propositions ofbounded rationality (NOBRE, 2008), by carryingthe meaning of:

(a) Lack of information, which leads the orga-nization to unpredictability of outcomes.

(b) And, insufficiency of cognitive abilities forgeneral information-processing.

The former, lack of information, means that:

Definition 1: Uncertainty is the difference be-tween the total amount of information that theorganization needs to have in order to complete atask, and the amount of information in possessionof the organization.

The latter, insufficiency of cognition, mansthat:

Definition 2: Uncertainty is the difference be-tween the degree of cognition that the organizati-on needs to have in order to complete a task, andthe degree of cognition in possession of the orga-nization.

These two approaches to uncertainty com-plement each other and this paper proposes that:

Proposition 1: The greater the amount of in-formation that the organization needs to have inorder to perform and to complete a task, the gre-ater is the degree of cognition that the organizati-on needs to have in order to process and to ma-nage this information for task execution and com-pletion.

Figures 2 and 3 illustrate such concepts ofuncertainty using symbolic scales of measurement.



Figure 3

Uncertainty as Lack of Cognition

Therefore, the question which rises in our questis: - what to do in order to reduce the level ofuncertainty that the organization confronts andneeds to manage? Organizational cognition andorganization design have together an important rolein the answer of this task (NOBRE, 2005, 2008).

ORGANIZATIONAL COGNITION

The Domain of Organizational Cognition

Like perception and emotion, cognition is aprocess or a set of processes that subsumeattention, knowledge organization, decision-makingand problem-solving. In such a way, the degree ofcognition is synonymous with the level ofelaboration and integration of such a set ofprocesses.

Organizations resemble cognitive systemswhen they present abilities and processes forsensing, perceiving, filtering and attention; storingand organizing knowledge; problem solving,decision-making and learning. These processes areevoked by internal and external stimuli to theorganization.

The perspective of organizations as lateral andvertical distributed cognitive agents was firstlytouched upon in the work of March & Simon

(1958, 1993). Later, this perspective was furtherextended to the concept of ComputationalOrganization Theory (COT) in the work of Carley& Gasser (1999). This paper adopts theseperspectives and it views the structure of theorganization resembling a nexus of cognitive agentsand processes which are organized through lateraland vertical relations. These cognitive agents arethe participants within the organization and theycan subsume humans and cognitive machines(NOBRE, 2008). Agents also can represent adepartment, a division, a unit, or any part in theorganization. They exchange information betweenthem and with the organization environmentthrough the use of protocols of communication,and they are coordinated according to theorganization’s social structure.

In a broad sense, cognition develops in orderto increase the probability of humans to survive(PLUTCHIK, 1982). Similarly, organizationalcognition has the same function.

Human vs. Organizational Cognition

Human cognition is part of a natural systemand hence it is not a man-made system. Therefore,the brain and the cognitive abilities of humans aremore or less unchangeable.

Organizational cognition is part of an artificialsystem which is designed and hence it is a man-made system. Moreover, this type of systeminvolves humans and machines. The cognitiveabilities of organizations can be changed andimproved through the process of organizationdesign. Therefore, organizational cognition iscontingent upon the goals, social structure,participants, technology and the environment ofthe organization.

The Discipline of Organization Cognition

A theory of organizational cognition is importantand necessary when we decide to designorganizations with higher capabilities of informationprocessing and uncertainty management. In such



1 In resume, Knowledge Management (KM) subsumes a set of practices used by organizations to identify, create, represent,organize, and distribute knowledge for reuse, awareness and learning. In this paper perspective, KM is a sub-process of Organi-zational Cognition (OC), since this latter (OC) involves the former (KM).2 Shortly speaking, organizational learning is a field within organizational theory that studies learning and adaptive models fororganizations.

a way, organizational cognition is a discipline whichcontributes to improve the computational capacityof the organization along with its ability forknowledge management (NOBRE et al., 2008).

Organizational cognition is concerned with theprocesses which provide agents and organizationswith the ability to learn, to make decisions and tosolve problems. The main agents of organizationalcognition are the participants within theorganization and the social networks which theyform. In organizations, cognitive processes aresupported by their goals, technology and socialstructure. Moreover, organizational cognition is alsoinfluenced by inter-organizational processes andthus by the environment. Therefore, the choice ofthe organization elements, and thus organizationaldesign (GALBRAITH, 2002), plays a fundamentaltask in organizational cognition.

The cognition of the organization can berepresented as a matter of degree whose leveldepends on the choice of the organizationelements.

Ten Principles of Organizational Cognition

This section summarizes ten principles oforganizational cognition which form the basis forthe definitions, premises and propositionsproposed in this paper. They are enumerated as:

(i)Organizational cognition is concerned withthe processes which provide agents andorganizations with the ability to learn, to makedecisions and to solve problems.

(ii) A theory of organizational cognition isimportant and necessary when we decide to designorganizations with higher capabilities of informationprocessing and uncertainty management.

(iii) Organizational cognition is a disciplinewhich contributes to improve the computationalcapacity of the organization along with its abilityfor knowledge and uncertainty management.

(iv) The main agents of organizational cognitionare the participants within the organization and thesocial networks which they form. Agents subsumehumans and cognitive machines.

(v) Cognitive processes are supported by thegoals, technology and social structure of theorganization. Moreover, organizational cognition isalso influenced by inter-organizational processesand thus by the environment.

(vi) The cognition of the organization can alsobe represented as a matter of degree whose leveldepends on the choice of models of organizing.

(vii) The choice of organizing models, and thusorganization design, plays a fundamental role inorganizational cognition.

(viii) The capability of the organization forinformation processing, knowledge and uncertaintymanagement, task execution, and managementof complexities of the environment, depends onits degree of cognition.

(ix) The degree of cognition of the organizationdepends upon the choice of its elements, and thechoice of the organization elements depends uponthe environment. Consequently, organizationcognition is contingent upon the environment.

(x) Organizational cognition supportsknowledge management1 and organizationallearning2 with processes that contribute to improvecontinuously the elements, the competitiveadvantage, and the results of the organization. Suchresults subsume equilibrium between theparticipants’ motives and the organization goals;



customer satisfaction; organization performanceand profitability.

ORGANIZATIONAL INTELLIGENCE,AUTONOMY AND COMPLEXITY

Definitions of organizational intelligence,autonomy and complexity are briefly presented inthis section.

Organizational Intelligence

Intelligence is a general mental ability(SCHMIDT; HUNTER, 2000), which depends onrational and emotional processes. Organizationsalso pursue intelligence which is supported by theirinternal elements (participants, social structure,technology and goals). Additionally, like cognition,intelligence is a matter of degree. The relationshipbetween organizational intelligence and cognitionis defined by:

Proposition 2: The greater the degree ofcognition of the organization, the greater is itschance to exhibit intelligent behavior.

Organizational Autonomy

This paper regards autonomy as the ability ofan organism to act through the use of cognition.Additionally, like cognition and intelligence,autonomy is a matter of degree. Therefore, itproposes that:

Proposition 3: The greater the degree ofcognition of the organization, the greater is itsautonomy.

Organizational Complexity

This paper regards the level of complexity ofthe organization as contingent upon its degree ofcognition. Therefore, the complexity of organizationsare synonymous with their cognitions which areprocesses used to solve complex tasks. Hence, itis proposed that:

Proposition 4: The greater the degree ofcognition of the organization, the greater is its abilityto solve complex tasks.

ENVIRONMENTAL COMPLEXITY

The complexity of the environment iscontingent upon the level of uncertainty that itrepresents to the organization. Similarly, thecomplexity of a task environment is contingentupon the level of uncertainty that it represents tothe organization during task execution andcompletion. Therefore:

Proposition 5: The greater the level of taskcomplexity, the greater is the level of taskuncertainty.

Proposition 6: The greater the level ofenvironmental complexity, the greater the level ofenvironmental uncertainty.

Proposition 7: The greater the level ofenvironmental complexity, the greater is the levelof environmental uncertainty that the organizationconfronts and needs to manage.

ORGANIZATIONAL COGNITION AND THEENVIRONMENT

This section presents premises in order tosupport propositions that relate the organizationand the environment.

Premise 1: The elements of the organization(participants, social structure, technology andgoals) support the organization with cognitiveprocesses such as filtering and attention, storingand organizing knowledge, problem solving,decision-making and learning.

Premise 2: The degree of cognition of theorganization is contingent upon the level ofelaboration and integration of the organizationprocesses.

Premise 3: The level of complexity of theorganization is contingent upon its degree ofcognition.

Therefore, it is proposed that:

Proposition 8: The higher the level ofcomplexity of the organization, the higher is itsdegree of cognition.



Proposition 9: The higher the degree ofcognition of the organization, the lower is therelative level of environmental complexity.

Proposition (9) does not mean that the levelof complexity of the environment reduces, but thatsuch a level of complexity is relatively reducedwhen compared to the growth in the level ofcomplexity of the organization. Therefore, byassociating propositions (7) and (9), it can bestated that:

Proposition 10: The lower the relative level ofenvironmental complexity, the lower is the relativelevel of environmental uncertainty that theorganization confronts and needs to manage.

Similarly, proposition (10) states that thelevel of uncertainty in the environment is relativelyreduced if an increase in the degree of cognitionof the organization occur. Therefore, the nexttheorem can be deduced from the previous chainof propositions:

Theorem 1: The higher the degree of cognitionof the organization, the lower is the relative levelof environmental complexity and uncertainty thatthe organization confronts and needs to manage.

HIERARCHIC LEVELS OF COGNITION INORGANIZATIONAL SYSTEMS

Studies of complex systems and theirclassification through hierarchical levels ofcomplexity were proposed in (BOULDING, 1956;SIMON, 1996). In these studies, a system isdefined as a large number of objects together withrelationships between them and between theirattributes or properties. The parts, elements orobjects which form the systems vary from beingvery simple to very complex in structure, and frombeing highly stable to highly dynamic and variablein their interaction. Moreover, each system of higherlevel of complexity incorporates the features ofthose systems below it.

In such a context, this paper proposes thatdifferences in the levels of complexity of systems

reside not only in the properties and structure oftheir elements, but most importantly, in the abilitiesof these elements. The former, i.e., properties andstructure, refers to physical, biological and chemicalattributes of the system, and the latter, i.e., abilities,means cognition, intelligence and autonomy of thesystem.

Therefore, by analyzing the Boulding’s typologythat classifies systems according to their levels ofcomplexity, it becomes evident to conclude thatthe higher the complexity of a system in theBoulding’s classification scale, the higher is itsdegree of cognition, intelligence and autonomy.This classification of systems is enumerated from1 to 9 in the order of growth of their levels ofcomplexity (BOULDING, 1956):

(1) Frameworks: systems comprising staticstructures, such as the arrangements of atoms ina crystal or the anatomy of an animal.

(2) Clockworks: simple dynamic systems withpredetermined motions, such as the clock and thesolar system.

(3) Cybernetic Systems: systems capable ofself-regulation in terms of some externallyprescribed set point or target, such as a thermostat.

(4) Open systems: systems capable of self-maintenance based on a through-put of resourcesfrom their environment, such as living cells.

(5) Blueprinted-growth systems: systems thatreproduce not by duplication but by the productionof seeds or eggs containing pre-programmedinstructions for development, such as the eggchicken system.

(6) Internal-image systems: systems capableof a detailed awareness of the environment inwhich information is received and organized intoan image or knowledge structure of theenvironment as a whole. Animals function at thislevel.

(7) Symbol-processing systems: systems thatpossess self-consciousness and are capable ofusing language. Humans function at this level.



3 The subject of emotions in organizations is left for further research. Perspectives about this topic can be found in (Bagozzi, etal 1998; Fineman, 1993; Keltner & Gross, 1999; Keltner & Haidt, 1999; Plutchik, 1982; Scherer, 1982).4 The term satisfice was coined by Herbert Simon (March & Simon, 1958). In resume, satisficing is a decision-making strategywhich attempts to meet criteria for adequacy, rather than to identify an optimal solution.

(8) Social systems: systems comprising agentsfunctioning at level 7 who share a common socialorder and culture. Organizations operate at this level.

(9) Transcendental systems: systemscomposed of the absolutes and the inescapableunknowable.

According to this typology, levels 1 to 3 includethe physical systems whose structures are highly rigid,constrained and limited. Levels 4 to 6 subsume thebiological systems. Levels 7 to 8 involve the humanand social systems. The level 9 is any imaginary level.Moving from level 1 to 8, the systems becomeprogressively more complex and their structuresbecome somewhat less rigid and constrained, andthe connections between the interacting partsbecome relatively loose, where less constraint isplaced on the behavior of one element by thecondition of the others (SCOTT, 1998). Additionally,and most importantly, moving from level 1 to 8, thesystems grow towards higher degrees of cognition,intelligence and autonomy.

From such analyses, it can be asserted thatdifferences between theories of natural and socialsciences reside not only in the properties andstructure of their elements of study, but mostimportantly, in the abilities of these elements. Theformer refers to physical, biological and chemicalattributes, and the latter means abilities to cognition,intelligence and autonomy. On one hand, the mainelements of social systems are humans and networksof people, and also organizations and networks oforganizations. Social systems possess high degreesof cognition, intelligence and autonomy which aredistributed among their individuals and among theirrelationships. On the other hand, the elements of,and the relationships with, physical, biological andchemical systems, including all the objects andorganisms of the ecological system, but excluding

the man, are less complex than those found in socialsystems if we consider that they have low degreesof cognition, intelligence and autonomy (if any inmost of the cases).

Therefore, the nature of a theory oforganizations resides in principles of humanbehavior and cognition3.

COGNITIVE DEFINITIONS OF THE ORGANIZATION

Organizations as Distributed Cognitive Agents

The definition of organizations introduced inthis subsection represents a synthesis of theconcepts presented in (CARLEY; GASSER, 1999;MARCH; SIMON, 1958; NOBRE et al., 2008;SCOTT, 1998).

Firstly, organizations are assemblages ofdistributed cognitive agents. Agents are classified asnatural or artificial, and living or nonliving. Humansare natural-living agents, while machines, and morespecifically cognitive machines (NOBRE, 2005), areartificial-nonliving ones. Agents have cognitive,physical, temporal, institutional and spatial limitations(CARLEY; GASSER, 1999; NOBRE, 2008).

Secondly, organizations pursue a coordinativesystem rooted into a social structure which iscomposed by normative and behavioral parts(SCOTT, 1998). Coordinative systems of distinctorganizations have different degrees ofcentralization and decentralization.

Thirdly, organizations pursue goals. Theconception of goals varies from individual toorganizational levels and also from technical,managerial and institutional to worldwide levels(NOBRE, 2008). The meaning of goals can rangefrom the perspectives of rational, natural to opensystems. Additionally, the strategy of satisfice4 which



5 A tutorial on strategic reward systems is found in (Dunnette & Hough, 1992: 1009-1055).6 A Unified Model of Employee Motivation is presented in (Elding et al, 2006).

attempts to meet criteria for goal adequacy, ratherthan goal optimization, is better applied to theorganization since agents have limitations ofcognitive resources to maximize (MARCH; SIMON,1993).

Lastly, organizations are open systems, andtherefore they pursue the skills of sensing from,and responding to the environment.

In conclusion, organizations are assemblagesof distributed and interacting agents with acoordinative system. They are supposed to satisfygoals, and they have relations with theenvironment. In such a context, the term “satisfy”is synonymous with “satisfice” as defined by Simon(1997a).

Characteristics of the Organization

(i) The members of organizations are cognitiveagents that participate in decision-making, problemsolving and learning processes in the organization(MARCH; SIMON, 1993; NOBRE et al., 2008;SIMON, 1997b).

(ii) Processes of decision-making involve trade-offs among alternatives which are characterizedby uncertainty, incomparability and unacceptability,and hence they can lead organization membersto intra-individual conflict. Additionally, membersof groups in organizations differ in their perceptionsand goals, and thus they can disagree in theirdecisions causing group conflicts (MARCH; SIMON,1993; NOBRE, 2008).

(iii) The intra-individual and group conflictswhich arise in organizations as exposed in (ii) aremainly determined by uncertainties and lack ofinformation, and most importantly by cognitivelimitations of humans. Hence, these conflictscannot be solved by incentive and reward systems5.Such cognitive and information constraints aresynonymous with bounded rationality (MARCH,

1994; MARCH; SIMON, 1993; NOBRE, 2008;SIMON, 1982, 1997a, 1997b). However, asproposed in (NOBRE, 2005, 2008; NOBRE et al.,2008), cognitive machines can be used to reduceor to solve such conflicts in organizations.

(iv) The members of organizations havedifferent perceptions. Such a differentiation isaccentuated due to the variety of individualmotives6, and also because of the inequality ofdistribution of information among the participantsin the organization. Therefore, it can lead theparticipants within the organization to groupconflicts (MARCH; SIMON, 1993; NOBRE, 2008).

(v) The members of organizations havemotives which differ from organization goals.Hence, organizations have to motivate them andto provide them with inducements (such asincentive and reward systems) which lead themto participate in organization activities, includingdecision-making, problem-solving and learning. Ifsatisfactory alignment is found between theorganization’s goals and its participants’ motives(GIBBONS, 1998), then organization equilibriumcan be achieved (MARCH, SIMON, 1993; NOBRE,2008).

(vi) Organizations shape participants’perceptions and behavior through social structure,technology and goals, and participants shapeorganizations through their culture, behavior,emotions, perceptions, motives and cognitive skills.

(vii) The environment shapes the socialstructure, technology, goals, participants andbehavior of organizations, through its sources ofcomplexity and uncertainty, and also throughinformation, processes, technologies, among otherelements.

(viii) Organizations also shape the environmentthrough similar means.



Figure 4

The Organization Levels of Analysis

7 Processes of this kind can also involve process improvement models like CMM (Paulk et al , 1994), quality procedures like ISO9000 and 14000, principles of management and production like just-in-time and lean-production, intranet and the knowledgeto be shared within the organization, policies for recruiting and hiring agents (participants), procedures for evaluating agents andperformance, etc.

Organizations as Hierarchic Cognitive Systems

The classification of the organization intechnical, managerial and institutional levels ofanalysis was initially proposed by Talcott Parsons(PARSONS, 1960). This paper borrows andsupports his ideas and it also extends them toinclude a fourth level of analysis named worldwide

system. Moreover, these levels of analysis are

introduced here in the context of cognitiveorganizational systems. Their meanings aredescribed by the following paragraphs and Figure4 illustrates the organization under such aperspective.

Technical Level

The technical system is concerned withcognitive tasks and general activities used for thedevelopment of goods and services. It comprisespeople, machines, communication systems andprocesses. This level depends on information andresources of the environment for the acquisitionof new technologies, and also for theacknowledgement of compliance of goods andservices with customers’ requirements, technical,quality and general standards.

Managerial Level

The managerial system is concerned withcognitive tasks of analysis, design and redesign ofthe organization. In this level, the organizationcarries out activities of planning, control,coordination and innovation in the areas of goalsand strategy; structure (normative structure,specialization, span of control, distribution ofauthority, departmentalization, etc.); technologyand processes7 of acquisition, organization,processing, communication and sharing of



information along with decision-making andlearning; rewards (incentives and inducements);and human resources (recruiting, training, etc.). Thislevel also needs a channel of communication withthe environment in order to exchange informationthrough practices benchmarking and otherstrategies. In such a way, the organization is in thepursuit of competitive advantage and acquisitionof information such as on marketing strategies andthe incentive and reward systems offered by otherorganizations and competitors. By connecting withthe environment, the organization also can hirenew talents, select and form new partnerships withbuyers and suppliers, among other tasks. Themanagerial level is also a mediation level betweentechnical and institutional systems.

Institutional Level

The institutional system is concerned withcognitive tasks used to mediate between theorganization and its environment. It comprises theunderstanding of the social, political, cultural andeconomic contexts of the organization’senvironment. The cognitive tasks at this level shapeboth the technical and the managerial systems,and also the environment. At this level, participantshave responsibility to understand regulativeprocesses of the market which constrain theboundaries of action of the organization; tounderstand the cultural aspects of the organizationand its environment; to manage the relationshipsbetween the organization and the networks oforganizations which influence upon the businessof the prime organization; to understand tax ruleson the transaction of goods and services, laborunion rights and laws; to set up broader goals andstrategies for the organization, like its expansion toother geographical locations and markets,delineation of new products and services; to attract

and to maintain a body of stakeholders; to formnew joint ventures and partnerships; to analyzethe wealth of the organization; to plan thepercentage of the stocks to be shared in the market;to participate in the decision processes of designand redesign of the organization; among othertasks.

Worldwide Level

The worldwide system is concerned withcognitive tasks which connect the organization tothe world and to the globalization. Such tasksinvolve the analysis of the implications oforganizations, networks and populations oforganizations for the social, cultural, economic,political and ecological contexts of the environment.It provides general analysis on the implications oforganizations for the whole economy, for the worldincome distribution, for the Gross Domestic Product(GDP) per capita of a country, for people’s sociallife, well-being, wealth and health, for the globalecosystem and its natural resources; for climatechange and energy demand; and so on. Someprominent studies related to this level of analysisare presented in (EASTERLIN, 2000; JOHNSON,2000; JONES, 1997; PRITCHETT, 1997; WORLDBANK, 2003).

MODELS OF COMPLEX ORGANIZATIONALSYSTEMS

Complex Model of the Organization

Definition 3: The organization is a special typeof dynamic system8 characterized by a level ofcomplexity CL which is contingent upon its degreeof cognition Cd, intelligence Id and autonomy Ad.

Axiom 1: Considers that CL is the level of

complexity of an organization Os and that C

d, I

d

8 A dynamic system has time-varying interactions (Forrester, 1961). This paper views systems as defined in (Bunge, 1987; andHall & Fagen, 1956). Additionally, it considers the organization as a system with memory - i.e. given the state of an organizationOs at a discrete time k, then it is assumed that Os(k+1) = Os(k) + Os(k-1).



and Ad are its degrees of cognition, intelligenceand autonomy respectively. Moreover, assumesthat CL can be characterized by a function g ofparameters Cd, Id and Ad:

(1)

CL,, C

d, I

d and A

d are defined in the interval

[0,1] since they can be characterized by using theconcepts of fuzzy sets and membership functions1

(ZADEH, 1965). The application of the fuzzy setstheory is encouraged to this definition of organiza-tions because complexity, cognition, intelligenceand autonomy are vague and loose concepts inthe sense defined by Black (1937, 1963), andthey also are fuzzy concepts in the way definedby Zadeh (1965, 1973). Therefore, C

L , C

d , I

d and

Ad can be represented as matters of degree in the

continuous interval [0,1].

Axiom 2: In such a way, let us define an orga-nization O

s denoted here by an object u belon-

ging to an universe of discourse U, which containsthe all classes of organizations, i.e., (u

iiiii Î U |

iiiii=1,…,N), for N integer.

Axiom 3: Let us also define the level of com-plexity C

L, and the degrees of cognition C

d, intelli-

gence Id and autonomy A

d as fuzzy sets with their

respective membership functions denoted byµ

CL(u), µ

Cd(u), µ

Id(u) and µ

Ad(u) ∈ [0,1], i.e.:

CL = {u | µCL(u) ∈ [0,1], u ∈ U} (2)

Cd = {u | µCd(u) ∈ [0,1], u ∈ U} (3)

Id = {u | µId(u) ∈ [0,1], u ∈ U} (4)

Ad = {u | µAd(u) ∈ [0,1], u ∈ U} (5)

Therefore, Os can assume four degrees of com-plexity, intelligence, cognition and autonomy res-pectively, where such degrees can be interpretedas degrees of compatibility or membership of Os

to the respective fuzzy sets CL, Cd, Id and Ad.

From equation (1), it can be stated that:

Definition 4: The level of complexity CL is a

function g which can be represented by a t-norm ”or an s-norm

(DUBOIS, PRADE, 1985), i.e.:

(6)

(7)

Complex Model of the Environment

This subsection and the next one are aboutthe environment e, and the relations R

e between

the organization Os and the environment e.

Axiom 4: Let us consider an organization Os1

with relations Re1

to an environment e1, (O

s1 ”! R

e1

”! e1), which has relations R

e2 to another environ-

ment e2, (e

1 ”! R

e2 ”! e

2). Therefore, a generic envi-

ronment en of an organization O

sn form relations

Re(n+1)

to an environment e(n+1)

, (Osn ”! R

e(n+1) ”!

e(n+1)

), where n is integer.

Axiom 5: Let us define a network NE constitu-

ted by (n+1) organizations Os(i=1,…,n+1)

. Let us alsodefine the organization O

s2 as the environment of

Os1

with relations Re1

between them, and Os3 as

the environment of Os2 with relations R

e2. Therefo-

re, it can be derived that Os(n+1)

is the environmentof O

sn with relations R

en between them: (O

sn ”! R

en

”! Os(n+1)

).

Axioms (4) and (5) also imply that an environ-ment is a relative concept that depends on the pers-pective of our analysis on a map of networks of or-ganizations. This means that the roles of e and O

s

may be exchanged since an environment e can re-present an organization O

s, and vice-versa, according

to perspective that someone looks at the map ofnetworks of organizations. Therefore:



Table 1

Classes of Relations Re(t)

Definition 5: Similarly to Os, definitions (3) and(4) also apply to the environment e, where Os isreplaced with e.

Complex Relations between the Organization andthe Environment

This subsection complements the definitionsof the organization Os and the environment e byintroducing different types of relations Re whichcan exist between them. It borrows and adaptsthe approach to the analysis of ecological dyna-mics presented in (BOULDING, 1978) in order todescribe the diversity of relations Re.

Axiom 6: Lets us assume an organization Os(t)with a set of state variables denoted by XXXXX(t), whe-re t denotes time. Additionally, let us define theorganization performance POs(t) as a measure of itsefficacy and efficiency which are dependent onthe behavior of XXXXX(t).

Axiom 7: Similarly, let us consider an environ-ment e(t) with state variables YYYYY(t) and with per-formance denoted by P

e(t), which holds the same

assumptions given to POs(t)

.

Axiom 8: Let us assume that Os(t) can affect

e(t) in three ways. Os(t) may affect e(t) favorably,

and hence the relation Re(t) is cooperative. A rise

in POs(t) will increase Pe(t) (i.e., if POs(t) ‘! then Pe(t) ‘!).Secondly, the relationship Re(t) may be competiti-ve. In this case, a rise in POs(t) leads to a decline inPe(t) and a fall in POs(t) causes a rise in Pe(t) (i.e., ifPOs(t) ‘! then Pe(t) “! and if POs(t) “! then Pe(t) ‘!). Thir-dly, Pe(t) may have no dependence on POs(t) andtherefore a rise or a fall in POs(t) may have no effecton Pe(t) (i.e., if either POs(t) ‘! or “! then Pe(t)(0)).

Similar relations can be postulated for the in-fluence of e(t) on Os(t). In this case, new repre-sentations have to be derived. Therefore:

Axiom 9: Let us denote R(e’!Os)

as the relationsto the effect of e(t) on O

s(t), and R

(Os’!e) as the

relations of Os(t) on e(t).

The results of all possible combinations arerepresented in the Table 1, and Table 2 describesthe results of such combinations.

Definition 6: Relations Re are dynamical syste-

ms whose attributes can change over time. Exam-ples of attributes applicable to these relations arecompetition and cooperation. R

e does not guaran-

tee bilateral properties, i.e., the types of relationscreated from O

s(t) to e(t) as given by R

(Os’!e) may

differ from the relations of R(e’!Os)

. Moreover, defi-nitions (3) and (4) also apply to the concept ofrelations R

e between O

s and e.



Table 2

Analysis of Relations Re(t)

Complex Networks of Organizations

An important result derived from axiom (5)and definition (5) is the concept of networks oforganizations as outlined here.

Definition 7: A network of (n+1) organizationsO

s(i=1,…,n+1) is a dynamic system denoted by N

E(t)

whose relations Re(i=1,…,n+1)

change over time.

Relations between organizations and theenvironment, including other organizations and themarket, change over time. As an example, after theprivatization of the telecommunications market inBrazil in the late of 1990’s, most of thetelecommunications companies in that environmentlost part of their governmental customers, and sincethen, they had to find new solutions in order to survive(VOLPE; NOBRE, 2000).

CONCLUSIONS AND CONTRIBUTIONS

On Organizational Cognition

This paper put forwards cognition as afundamental element of the organization. Insummary, it proposed that:

(i) A theory of organizational cognition isimportant and necessary when we decide to designorganizations with higher capabilities of informationprocessing and uncertainty management. In such away, organizational cognition is a discipline whichcontributes to improve the computational capacityof the organization along with its ability for knowledgemanagement.

(ii) Organizational cognition plays an importantpart in organization design, and vice-versa, and alsoin the analyses of the relations between theorganization and the environment.

To support such statements, this papercontributed with definitions, premises andpropositions towards a theory of organizationalcognition which comprises concepts of intelligence,autonomy and complexity for the organization, theenvironment and their relations. It proposed tenprinciples about organizational cognition and it clearlydistinguished organizational cognition from theconcept of organizational learning. It also introducedthe concept of hierarchic levels of cognition inorganizational systems and thus it set up cognitionas a fundamental element of the organization.



On Organizational Cognition and EnvironmentalComplexity

This paper borrowed the picture oforganizations as contingent upon the environmentfrom the perspective of organization design andcontingency theory as proposed by Galbraith(1973, 1977, 2002). Moving further, it also reliedon the proposition that an increase in organizationalcognition reduces the relative levels of uncertaintyand complexity of the environment with which theorganization relates. Such perspectives weresummarized by theorem (1):

Theorem 1: The higher the degree of cognitionof the organization, the lower is the relative levelof environmental complexity and uncertainty thatthe organization confronts and needs to manage.

According to the concept of Hierarchic Levelsof Cognition presented in Section 9, organizationalsystems grow in complexity as they move fromframeworks, mechanical and biological systems tosocial systems. It was defined that cognition, andthus degree of cognition, is the main element whichmakes organizational systems distinct from eachother in terms of complexity, intelligence, autonomyand behavior. Organizations with higher degreesof cognition have higher levels of complexity alongwith higher degrees of intelligence and autonomy.Therefore, in this paper, organizational complexitywas defined as synonymous with, and contingentupon, organizational cognition; and environmentalcomplexity was defined as synonymous with, andcontingent upon, environmental uncertainty.

Moreover, it was defined that organizationalcognition is a matter of degree which is contingentupon organization design, i.e., the choice of theelements of the organization that subsume goals,social structure, participants and technology.Therefore, organizational cognition differs fromhuman cognition if we consider the perspectivethat the former is part of an artificial process ofdesign, while the latter is part of a natural andbiological process.

Additionally, as a consequence of thecontingency of the organization upon theenvironment, it was stated that organizations havedifferent degrees of cognition when they operatein different environments.

Further Extensions

On Measurements of Organizational Cognition

As important as a theory of organizationalcognition, is a complementary methodology tomeasure degrees of organizational cognition. Insuch a direction, the book research presented in(Nobre et al. 2008) has provided the literaturewith important directions to assess and to measurethe degree of organizational cognition with basison appraisal methods of continuous processimprovement models. In his book, Nobreinvestigated an industrial case study where heassociated the concept of degrees of organizationalcognition with levels of organizational processmaturity, capability and performance along withorganizational learning results. Qualitative analysesand quantitative measurements of the industrialcase study indicated that improvements in thelevels of organization process maturity andorganization process performance were associatedwith improvements in the degree of organizationalcognition; and also that improvement inorganizational learning could be associated withimprovements in organizational cognition. Thislatter association is reinforced in the literature whenimprovements in organization performance andproductivity are associated with the practices oforganizational learning (ARGOTE, 1999).

On the Future of Organizations

While the characteristics of the elements of theorganization will change, evolve and developcontinuously towards higher levels of cognition andcomplexity, the purpose of existence of theorganization will remain the same or will not changein the same proportion of its elements (NOBRE,2008).



>

Recebido em: jun. 2007 · Aprovado em: dez. 2007

Farley Simon Nobre

Founder & Director CEO of Innovation Technology EnterpriseThe School of Mechanical Engineering

The University of BirminghamEdgbaston, Birmingham, B15 2TT, UK

e-mail: [email protected]: +44 (0)121 414 4263

Andrew M. TobiasSenior Lecturer

The School of Mechanical EngineeringThe University of Birmingham

Edgbaston, Birmingham, B15 2TT, UKSite: http://www.eng.bham.ac.uk/mechanical/about/

people_tobias.shtmle-mail: [email protected]

Tel: +44 (0)121 414 4263

David S. WalkerSenior Teaching Fellow

Birmingham Business SchoolThe University of Birmingham

Edgbaston, Birmingham, B15 2TT, UKSite: http://www.business.bham.ac.uk/staff/walkerd.shtml

e-mail: [email protected]: +44 (0)121 414 8322

REFERENCES

ARGYRIS , C . ; SCHÖN, D . A .Organizational learning: a theory ofaction perspective. [S. l.]:Addison-Wesley, 1978.

BAGOZZI, R. P. et al. Goal-directedemotions. Cognition and Emotion, [S.l.], v. 12, n. 1, p. 1-26, 1998.

BERNSTEIN, D. A. et al. Psychology.[S. l.]: Houghton Mifflin Company,1997.

BLACK, M. Vagueness: an exercise tological analysis . Phi losophy ofScience , v. 4, p. 427-455, 1937.

BLACK, M. Reasoning with loose

concepts. Dialogue , v. 2, p. 1-12,1963.

BLANNING, R. W.; KING, R. K. AI inorganizational design, modeling, andcontrol. [S. l.]: IEEE Comp. Soc. Press,1996.

BLAU, P. M.; SCOTT, W. R. Formalorganizations: a comparativeapproach. [S. l.], Routledge, 1963.

BOULDING, K. E. General systemstheory: the skeleton of science.Management Science, [S. l.], n. 2, p.197-208, 1956.

BOULDING, K. E. Ecodynamics: a new

theory of societal evolution . [S. l.],SAGE Publications, 1978.

BUCKLEY, W. Modern SystemsResearch for the Behavioral Scientist.[S. l.], Aldine Publishing Company,1968.

BUNGE, M.; ARDILA, R. Philosophyof Psychology. [S. l .] , Springer-Verlag, 1987.

CARLEY , K . M. ; GASSER, L .Computational OrganizationalTheory . In : WEISS , G . (Ed . ) .Multiagent systems: a modernapproach to distributed artificial

The former part, which is concerned with theelements of the organization, will move towards highlevels of automation, and it will include machineswith high degrees of cognition, intelligence andautonomy, mainly in those areas at upper layers andlevels of the organization; and thus they will provideorganizations with more capabilities of computationalcapacity along with knowledge and uncertaintymanagement. Therefore, new organizations of thiskind will be able to operate in, and to manage higherlevels of environmental complexity than organizationsof today. These transformations towards neworganizations will have implications for the societyand this is a topic of further research (NOBRE et al.,2008).

The latter part, which is concerned with thepurpose and the existence of organizations, willremain the same and for sure will not change in thesame proportions to the evolutions in the organizationelements. This is because the individual motives andthe organizational goals which are pursued by humankind will not change over time into the political,economical and social facets of this world.



intelligence. [S. l.], The MIT Press,1999. p. 299-330.

DIERKES, M.; ANTAL, A. B.; CHILD,J . ; NONAKA, I . Handbook oforganizational learning andknowledge. [S. l.], Oxford UniversityPress, 2003.

DUBOIS, D.; PRADE, H. A review offuzzy set aggregation connectives.Information Sciences, [S. l.], v. 36, p.85-121, 1985.

DUNNETTE, M. D.; HOUGH, L. M.Handbook of industr ia l andorganizational psychology. [S. l.]:Consulting Psychologists Press, Inc.,1992. v. 3.

EASTERLIN, R. A. The worldwidestandard of living since 1800. TheJournal of Economic Perspectives, [S.l.], v. 14, n.1, p. 7-26, 2000.

ELDING, D.; WALKER, D. S.; TOBIAS,A. M. towards a unified model ofemployee motivation, StrategicChange, [S. l.], v. 15, n. 6, 2006.

F INEMAN, S . Emotions inorganizations . [S . l . ] : SAGEPublications, 1993.

FORRESTER, J . W. Industr ialdynamics. [S. l.]: The MIT Press, 1961.

GALBRAITH, J. R. Designing complexorganizations. [S. l . ] : Addison-Wesley, 1973.

GALBRAITH, J . R . Organizationdesign. [S. l.]: Addison-Wesley, 1977.

GALBRAITH, J . R . Designingorganizations - an executive guideto strategy, structure, and process.[S. l.]: Jossey-Bass, 2002.

GIBBONS, R. Incentives inOrganizat ions . The Journal ofEconomic Perspectives, [S. l.], v. 12,p. 115-132, 1998.

GOLEMAN, D. Emotional Intelligence:Why it can matter more than IQ. [S.l.]: Bantam Books, 1994.

HALL, A. D.; FAGEN, R. E. Definitionof System. In: BUCKLEY, W. (Ed.),Modern systems research for thebehavioral scientist. [S. l.]: AldinePublishing Company, 1956.

HODGE, B. J.; ANTHONY, W. P.;GALES, L. M. Organization theory -

a strategic approach. [S. l.]: Prentice-Hall, 2003.

IANDOLI, L.; ZOLLO, G. Organizationalcognition and learning: buildingsystems for the learning organization.[S . l . ] : Information SciencePubl ishing, 2007.ISBN:9781599043135.

JOHNSON, D. G. Population, food,and knowledge. The AmericanEconomic Review, [S. l.], v. 90, n.1,p. 1-14, 2000.

JONES, C. I. On The evolution of theworld income distribution. TheJournal of Economic Perspectives, [S.l.], v. 11, n. 3, p. 19-36, 1997.

KELTNER, D.; GROSS, J. Functionalaccounts of emotions. Cognition andEmotion, [S. l.], v. 13, n. 5, p. 467-480, 1999.

KELTNER, D. ; HAIDT, H. Socialfunctions of emotions at four levelsof analysis. Cognition and Emotion,[S. l.], v. 13, n. 5, p. 505-521, 1999.

KHANDWALLA, P . N. Design oforganizations. [S. l.]: Harcourt BraceJovanovich, 1977.

KLIR, G. J.; FOLGER, T. A. fuzzy sets,uncertainty , and information .Englewood Cliffs, N.J: Prentice Hall,1988.

LA PORTE, T. R. Organized SocialComplexity: Challenges To Politicsand Pol icy. [S . l . ] : Pr incetonUniversity Press, 1975.

LANT , T . K . ; SHAPIRA, Z .Organizational cognit ion:computation and interpretation. [S.l.]: Lawrence Erlbaum Associates,2001. ISBN 0805833331.

MARCH, J .G . Handbook ofOrganizations. [S. l.]: Rand McNally& Company, 1965.

MARCH, J. G. A Primer on DecisionMaking: How Decisions Happen. [S.l.]: The Free Press, 1994.

MARCH, J. G.; OLSEN, J. P. TheUncertainty of the Past:Organizational Learning underAmbiguity. European Journal ofPolitical Research, [S. l.], n. 3, p. 147-171, 1975.

MARCH, J . G . ; S IMON, H . A .Organizations. [S. l.]: John Wiley &Sons, Inc., 1958.

MARCH, J . G . ; S IMON, H . A .Organizations . 2nd ed. [S. l.]: JohnWiley & Sons, Inc., 1993.

MCKINLAY, J. B. Processing people:cases in organizational behaviour. [S.l.]: Holt-Blond Ltd., 1975.

MILGROM, P . ; ROBERTS, J .Economics , Organizations &Management. [S. l.]: Prentice-HallInc., 1992.

MINSKY, M. (1986) The Society ofMind. [S. l.]: Picador, 1986.

NOBRE, F. S. Organizational systems:towards a unified theory. Seminarpresented for the art i f ic ialintelligence research group of theDepartment of Computer Sciences inthe Humboldt University of Berlin.Berlin: Johann von Newmann-Haus,2002.

NOBRE, F. S. Organizations andtechnology - past, present and futureperspectives. Seminar presented forthe Artificial Intelligence ResearchGroup of the Department ofComputer Sciences in the HumboldtUniversity of Berlin. Berlin: Johannvon Newmann-Haus, 2003a.

NOBRE, F . S . Perspect ives onorganizational systems: towards aunified theory. Doctoral Consortiumon Cognitive Science at the ICCM2003. Bamberg-Germany, April 09th

2003b.

NOBRE, F. S. Analysis and design oforganizational systems: towards a unifiedtheory. In: The t Conference of theAssociation of Brazilian Post-graduateStudents and Researchers in the UnitedKingdom (ABEP), Proceeding: 52, 1.,2004, Oxford. Proceedings… Oxford-UK,Oxford Centre for Brazilian Studies,2004a.

NOBRE, F. S. Analysis and design oforganizations - towards a theory oforganization cognition . Seminarpresented at the Birmingham BusinessSchool/Centre for International Businessand Organization Research (CIBOR).Birmingham-UK, Nov. 2004b.



NOBRE, F. S. On Cognitive machinesin organizations. 2005, 343 f. PhDThesis - University of Birmingham -Birmingham-UK, 2005. BirminghamMain Library, Control Number:M0266887BU.

NOBRE, F. S. Cognitive Machines inOrganizations: Concepts andImplications. Germany: VDM-VerlagPubl i sh ing , 2008. ISBN: 978-3639068627.

NOBRE, F . S . ; TOBIAS , A . M. ;WALKER, D. Organizational andTechnological Impl icat ions ofCognitive Machines: DesigningFuture Information ManagementSystems. [S. l.]: Information SciencePublishing - IGI Global , 2008.Forthcoming in December 2008.ISBN: 978-1-60566-302-9.

PARSONS, T. Structure and Processes inModern Societies. [S. l.]: Free Press, 1960.

PAULK, M. C. et al. The capabilitymaturity model: guidelines forimproving the software process. [S.l.]: Addison Wesley Longman, Inc.,1994.

PLUTCHIK, R. A psychoevolutionarytheory of emotions. Social ScienceInformation , 21: 529-553, 1982.

PRIETULA, M. J.; CARLEY, K.; GASSER,M . Simulating Organizations:Computational Models of Institutionsand Groups . [S. l.]: AAAI Press / TheMIT Press, 1998.

PRITCHETT, L. Divergence, Big Time.The Journal of Economic Perspectives ,[S. l.], v. 11, n. 3, p. 3-17, 1997.

PUGH, D. S. Organization Theory:Selected Readings. [S. l.]: PenguinBooks, 1997.

PUGH, D. S.; HICKSON, D. J. Writerson Organizations. [S. l.]: PenguinBooks, 1997.

SCHERER, K. R. Emotion as a process:Function, origin, and regulation.Social Science Information, [S. l.]: n.21, p. 555-570, 1982.

SCHMIDT, F. L.; HUNTER, J. E. SelectIntelligence. In: LOCKE, E. A. (Ed.).The Blackwell handbook of principlesof organizational behavior. [S. l.]:Blackwell Publishers Ltd., 2000. p. 3-14.

SCOTT, W. R. Organizations: rational,natural, and open systems. [S. l.]:Prentice Hall, Inc., 1998.

SENGE, P. The fifth discipline: theart and practice of the learningorganization. New York: Doubleday,1990.

S ILVERMAN, D . The theory oforganizations. [S. l.]: Heinemann,1970.

SIMON, H. Administrative behavior:a study of decision-making processesin administrative organization. NewYork: Macmillan, 1947.

SIMON, H. A. Models of boundedrationality: behavioral economics andbusiness organization. [S. l.]: MITPress, 1982. v. 2.

SIMON, H. A. The sciences of theartificial. 3rd ed. [S. l.]: The MIT Press,1996.

SIMON, H. A. Models of boundedrationality: empirically groundedeconomic reason. [S. l.]: MIT Press,1997a. v. 3.

S IMON, H . A . Administrat ivebehavior: a study of decision-makingprocesses in administrativeorganizations. [S. l.]: The Free Press,1997b.

TRIST , E . L . The evolut ion ofsociotechnical systems as aconceptual framework and as anaction research program. In: DE VEN,

Andrew Van; JOYCE, William (Ed.).Perspectives on Organization Designand Behavior. New York: Wiley-Interscience, 1981. p.19-75.

VOLPE, R.; NOBRE, F. et al. The roleof software process improvementinto tqm: an industrial experience.In: IEEE Proceedings of theInternational Engineer ingManagement Conference .Albuquerque-NM, [s. n.], 2000. p.29-34.

WORLD BANK. The little data book.[S. l.]: World Bank, 2003. ISBN 0-8213-5426-4.

WREN, D . A . The evolution ofmanagement thought. 3rd ed. [S. l.]:John Wiley and Sons, 1987.

ZADEH, L. A. Fuzzy sets. Informationand Control, [S. l.], v. 8, p. 338-353,1965.

ZADEH, L. A. Outline of a newapproach to the analysis of complexsystems and decision process. IEEETransactions on Systems, Man, andCybernetics, [S. l.], v. 3, n. 1, p. 28-44, 1973.

ZADEH, L. A. Fuzzy logic = computingwith words. IEEE Transactions onFuzzy Systems, [S. l.], v. 4, n. 2, p.103-111, 1996.

ZADEH, L. A. From computing withnumbers to computing with words –from manipulation of measurementsto manipulation of perceptions. IEEETransactions on Circuits and Systems,[S. l.], v. 45, n.1, p. 105-119, 1999.

ZADEH, L. A. A new direction in AI:toward a computational theory ofperceptions. AI Magazine, [S. l.], p.73-84, Spring 2001.

redalyc.a theory of organizational cognition: … · organizaÇÕes a theory of organizational...

Documents