The Complexities of the Automotive Industry: Positive and Negative Feedbacks in Production Systems

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Abstract. This paper utilizes complexity theory to analyze the implications of systemic changes that have occurred over the last 30 years in the automotive industry. We argue by dint of complexity analysis that the networked automotive production system characterized by just-in-time and lean production creates states far from equilibrium in individual parts manufacturers and assembly plants. Positive feedback creates system disturbances and adverse health and safety issues in the local plant environments. In addition, we examine four mechanisms that serve as negative feedback loops to absorb stresses in local plant environments and rectify health and safety related issues. This paper draws on thirty interviews with health and safety representatives at automotive manufacturing and assembly plants.

Resume. Ce papier utilise la theorie de complexite pour analyser les implications de changements systemiques qui se sont produits pendant les trente dernieres annees dans l'industrie automotrice. Nous soutenons, au moyen de l'analyse de complexite, que le systeme de production automoteur en reseau, caracterise par la production juste a temps et mince, cree des etats loin de l'equilibre dans les fabricants de parties individuels et les usines d'assembleur. Les retroactions positives creent des derangements dans le systeme qui causent des conditions defavorables de sante et securite dans les environs locaux de l'usine. En plus, nous examinons quatre mecanismes qui servent comme boucles de retroactions negatives pour absorber ces tensions environnementales, et resoudre les problemes de sante et securite. Ce papier est comprit de trente entretiens avec des representants de sante et securite venant des usines fabricants et d'assemblage automotrices.

INTRODUCTION

Over the last 30 years, the global automotive industry has gone through massive restructuring, with the conversion from a hierarchically oriented, vertically integrated bureaucracy to a horizontal network consisting of lead firms (in the North American context, Ford, Daimler-Chrysler and General Motors and Japanese transplants) and various levels of part suppliers. Concomitant with this shift is the global emergence of just-in-time and lean production and the diminution of mass production. While this new network arrangement promises greater organizational flexibility and these production programs offer efficiency over their predecessors, the combination brings greater levels of complexity. This paper follows the complexity turn in sociology (see Urry 2003; 2005a) and utilizes complexity theory to analyze the impact of these changes on the automotive industry. Complexity theory examines the physics of populations and their emergent and self-organizing systemic properties (Law and Urry 2004; Cilliers 1998). Using the tools developed in nascent theorizations of complexity, we analyze the emergence of the networked automotive production system and the nonlinear effects of this system on local plant environments and the workers who inhabit them. We argue, using complexity analysis, that the networked automotive production system of just-in-time and lean production creates states far from equilibrium in individual parts manufacturers and assembly plants. Lastly, we consider negative feedback mechanisms that attempt to stabilize the system.

Positive feedback, in the form of deficient preventative maintenance and housekeeping, produces health and safety issues in the local plant environments. Joint health and safety committees, collective bargaining agreements, the governmental system, and the International Organization for Standardization (ISO) TS16949 and 14000 standards serve as negative feedback mechanisms to absorb stresses to local plant environments and rectify health and safety related issues.

Our complexity analysis of the North American automotive industry, compared to typical Weberian and Marxist approaches to organizations, offers a theoretically nuanced conceptualization of the impact of internal disturbances on organizations and the effect of those internal disturbances on other organizations within a network. This analysis contributes to the current literature on complexity theory which has not been empirically grounded in the lived experiences of people affected by complex systems.

This paper is structured in six main sections. In the first section, we offer an overview of the contours of complexity theory and situate the complexity paradigm within past theoretical, epistemological, and ontological positions. In the following section, the metaphors and tools of complexity are defined. In the third section, we consider complex organizations as spaces of chaos and order and the shift from the vertically integrated bureaucracy to a networked morphology of organizations. This is succeeded by the methods of this study. In the fifth section, based on the data gathered from the health and safety representatives, we present and analyze the networked automotive production system consisting of just-in-time and lean production. In the final section, we examine the impact of positive and negative feedback in automotive production plants.

CONTOURS OF COMPLEXITY THEORY

According to Urry (2005a), a complexity turn in the physical "hard" sciences has made its way into the social sciences (see also, Urry 2003; Byrne 2005). This is based on the emergence of a more general "complex structure of feeling" that confronts some quotidian notions of social order (Maasen and Weingart 2000; Thrift 1999). Derived from chaos and systems theory, complexity theory is concerned with changes that do not fit into a simple linear law of distinct cause and corresponding effect (Byrne 1998). Unabashedly systems oriented, complexity theory stresses that there are various networked time-space paths, often immense disproportions between causes and effects, and volatile yet irrevocable patterns that seem to typify all social and physical systems (Urry 2003:7).

Complexity is a theoretical framework and ontology, insofar as it is grounded in the ontological claim that the contemporary, globalized world is complex. Systems in complexity theory occupy the space between order and chaos, that is, they are in balance (Cilliers 1998; Urry 2003, 2005b). (2) System components are never fully stabilized nor do they dissolve into anarchy. As Urry (2003:22) states, "there is a kind of 'orderly disorder' present within all such dynamic systems." Complexity theory is different from chaos theory which deals with simple, deterministic, nonlinear, dynamic closed systems that are sensitive to initial conditions. Complexity theory focuses on nonlinear open systems that interact with their environments (Gatrell 2004). Open systems interact with other systems and their environments producing various nonlinear effects.

In contradistinction to positivistic linear accounts, and crucial to complexity theory, is the position that knowledge is inherently local and contextual rather than universal (Byrne 2005; Cilliers 1998). Challenging the nomothetic project of positivism, complexity theory is dynamic, primarily concerned with description and explication of patterns of change in a given system and its particular local effects (Byrne 2005). Complexity theory also differs from the systems-based theories of Parsons and Luhmann. While systems theory focuses on problem solving, prediction, and control, complexity analysts undertake exploratory research focusing on explanation and understanding. In addition, while relations and networks figure in the work of systems and complexity theory, complexity places central importance on emergence and hybrids that result from systems (Gatrell 2004).

TOOLS AND METAPHORS OF COMPLEXITY THEORY

This recent complexity turn has been labeled (Urry 2004) the "new social physics." Metaphors and concepts are often drawn from quantum physics and its emphasis on nonlinear systems. Complexity theory places systems at the centre of analysis, examining how systems adapt and evolve as they self-organize through time (see Mitleton-Kelly 2003). A system in complexity theory comprises various components and subsystems embedded within systems that have their own respective components. An example of a system in social science (Gatrell 2004:2662) is a transport network that transfers people and materials from one place to another. Systems, then, include hybrids of social and material components, or in Lash and Urry's (1994) conceptualization, they are "material worlds." In a global sense, the world comprises various systems, functioning at manifold levels and scales, each comprising the environment for each other (Urry 2003; 2005b). A system is characterized as complex only when it consists of such intricate sets of nonlinear relationships and feedback loops that it cannot be analyzed as a whole (Cilliers 1998:3). (3) Focus is also on the effects of relations and connections between different elements.

A central tenet of complexity theory is that all living and social systems involve a process of self-making and self-organizing or autopoiesis. Autopoietic systems involve a network of production processes in which the role of each component is to participate in the production or transformation of other components in the network. In this sense, the network continually makes itself (Byrne 1998; Capra 1997; Prigogine 1997; Cilliers 1998; Gatrell 2004). A prime example of an autopoietic system is the Internet (Urry 2005b:246-7). Users across the globe, not business or state bureaucracies, are the key producers of the technology. "[The Internet] possesses an elegant, non-hierarchical rhizomatic global structure and is based upon lateral, horizontal hypertext links that render the boundaries between objects within the archive endlessly fluid" (Urry 2005b:247). From autopoietic systems, new structures and behaviours emerge vis-a-vis the continual interaction of system components (Holland 1998; Cilliers 1998).

Autopoietic systems characterized by emergence and hybridity are also far from balanced. Systems in complexity theory are nonlinear insofar as there is no consistent relationship between a specific cause and corresponding …