A new contingency view of the organization: mananging complexity and uncertainty through cognition.

AutorNobre, Farley Simon
CargoReport

INTRODUCTION

Studies of complex systems and their classification through hierarchical levels of complexity were proposed by Boulding (1956) and Simon (1996). In these studies, a system is defined as a large number of objects together with relationships between them and between their attributes or properties. The parts, elements or objects that form the systems vary from being very simple to very complex in structure, and from being highly stable to highly dynamic and variable in their interactions. Moreover, each system of higher level of complexity incorporates the features of those systems below it. In such a context, this paper proposes that differences in the levels of complexity of systems reside not only in the properties and structure of their elements, but most importantly, in the abilities of these elements. The former, i.e., properties and structure, refers to physical, biological and chemical attributes of the system, and the latter, i.e., abilities, means cognition, intelligence, autonomy, learning and knowledge management capabilities of the system.

Therefore, analyzing Boulding's (1956) typology, which classifies systems according to their levels of complexity, this research proposes that the higher the complexity of a system on Boulding's classification scale, the higher its degree of cognition (Nobre, Tobias, & Walker, 2009a, 2009b, 2009c). This classification of Boulding's systems, which is enumerated from 1 to 9 in the order of growth of their levels of complexity, is given as (1) frameworks, (2) clockworks, (3) cybernetic systems, (4) open systems, (5) blueprinted-growth systems, (6) internal-image systems, (7) symbol-processing systems, (8) social systems and (9) transcendental systems, respectively. According to this typology, levels 1 to 3 include the technical and physical systems. Levels 4 to 6 subsume the biological systems. Levels 7 to 8 involve the human and social systems. Level 9 is any imaginary level. Moving from level 1 to 8, the systems become progressively more complex and their structures become somewhat less rigid and constrained, and the connections between the interacting parts become relatively loose, where less constraint is placed on the behavior of one element by the condition of the others (Scott, 1998). Additionally, and most importantly, moving from level 1 to 8, the systems grow towards higher degrees of cognition.

From these analyses, it can be asserted that differences between theories of natural and social sciences reside not only in the properties and structure of their elements of study, but most importantly, in the abilities of these elements. On the one hand, the main elements of social systems are humans and networks of people, and also organizations and networks of organizations. Social systems possess high degrees of cognition and, consequently, high levels of intelligence, autonomy, learning and knowledge management capabilities, and whereas these abilities are distributed among their individuals and among their relationships. On the other hand, the elements of, and the relationships with, physical, biological and chemical systems, including all the objects and organisms of the ecological system, but excluding man, are less complex than those found in social systems if we consider that they have low degrees of cognition if any in most cases. Therefore, the nature of a theory of organizations resides in principles of human behavior and cognition(1).

Proceeding further, what makes this paper distinct and unique is that it puts forward a new analysis perspective of the organization and the environment, and also of the relations between them through the concepts of cognition and complexity. From this perspective, the paper proposes that cognition is the core asset of the organization since it contributes to control and to reduce the level of environmental complexity and uncertainty. It also contributes by explaining what distinguishes organizational cognition from the concepts of organizational intelligence, autonomy, learning and knowledge management. It most outlines the relations and frontiers between these concepts, and it explains that, despite being distinct, they form complementary abilities. These concepts, all together, form the set of abilities in the organization. Grounded in such a background, this paper presents a model of the organization as a set of fuzzy abilities; however, it also extends this model to the concept of the environment, relations between the organization and the environment, and networks of organizations.

ORGANIZATION, UNCERTAINTY AND COMPLEXITY

Environmental uncertainty can be associated with the level of uncertainty that the organization and its participants perceive or sense from the environment (Ducan, 1972). Moreover, the contingency theory (Galbraith, 1973, 1974, 1977, 2002) defines uncertainty as the variable which makes the organization(2)contingent upon the environment (3). Hence, organizational design, and thus organizational choice, depends on the concept of uncertainty. Briefly, uncertainty can be associated with the mathematical concepts of probability and fuzziness (Klir & Folger, 1988). However, uncertainty can also be associated with propositions of bounded rationality (Simon, 1982a, 1982b, 1997a, 1997b). In this latter perspective, uncertainty carries the meaning of lack of information(4), which leads the organization to unpredictability of outcomes, in addition to insufficiency of cognitive abilities for general information-processing and interpretation (Nobre et al., 2009a). The former, lack of information, means that uncertainty is the difference between the total amount of information that the organization needs to have in order to complete a task and the amount of information the organization actually possesses. The latter, insufficiency of cognition, means that uncertainty is the difference between the degree of cognition that the organization needs to have in order to complete a task and the degree of cognition in possession of the organization. These approaches to uncertainty are complementary to each other since the greater the amount of information that the organization needs to have in order to perform and complete a task, the greater is the degree of cognition that the organization needs to have in order to process and manage this information for task execution and completion. Therefore, the question which arises in our quest is: what can we do to control the level of uncertainty that the organization is faced with and needs to manage? This paper implies that organizational cognition plays an important role in such a task (Nobre et al., 2009a, 2009b, 2009c).

Complementarily to this view, this paper defines the complexity of the environment and being contingent upon the level of uncertainty that it represents to the organization. Similarly, the complexity of a task environment is contingent upon the level of uncertainty that it represents to the organization during task execution and completion. Therefore, it can be asserted that the greater the level of environmental complexity, the greater is the level of environmental uncertainty that the organization confronts and needs to manage (Nobre, 2005, 2008; Nobre et al., 2009a).

ORGANIZATIONAL ABILITY

Ability is a general term concerning the capacity to act mentally, physically, financially, legally or in some other way. Cognitive ability refers specifically to mental capacity (Ree, Carretta, & Steindl, 2002). In the context of this paper, cognitive ability involves processes and representations which support the pursuit of intelligence, autonomy, learning and knowledge management in the organization. Therefore, this paper sets cognition as the main element of organizational ability. From this viewpoint, abilities within the organization or, simply, organizational ability, involve concepts of cognition, intelligence, autonomy, learning and knowledge management. In the following subsections, this paper proposes concepts and principles of organizational cognition. It also reviews the concepts of organizational intelligence, autonomy, learning and knowledge management. In this review, the paper contributes to defining the frontiers between organizational cognition and the other organizational abilities.

Organizational Cognition

Overview

The subject of cognition in organizations has flourished over the last fifty years in an environment of extensive and multidisciplinary research influenced by developments in general systems theory, cognitive and social psychology, artificial intelligence and cognitive science, social psychology of organizations, sociology of knowledge, organizational learning and knowledge management. Most recently, this subject has been referred to as organizational cognition (Eden & Spender, 1998; Iandoli & Zollo, 2007; Lant & Shapira, 2001; Nicolini, 1999; Nobre et al., 2009a, 2009b; Porac & Thomas, 2002; Walsh, 1995).

Research on cognition in organizations has its roots in the publications of Simon (1947) on Administrative Behavior, and March and Simon (1958) on Organizations. In these publications, the organization was associated with information processing systems whose picture resembles a nexus of cognitive agents and processes organized through lateral and vertical relations. In this perspective, the organization benefits individuals and groups by extending their cognitive limitations to more advanced models of rationality (Simon, 1997a, 1997b). However, the meaning of this perspective has been separated by some researchers into two main streams: the computational and the interpretive approaches (Lant & Shapira, 2001). The computational approach investigates the processes by which the organization manipulates information, and associates the organization with information processing machines. In this stream, the emphasis is on information and efficiency. This approach is grounded in cognitive psychology, cognitive...

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