Multilevel Approach to Research in Organizations
- Micro approach
- Macro approach
- Micro-macro approach
- Hierarchy
- Multi Scale
- Multi Level
- Heterarchy
- Holarchy
- Holonomic
- Holons
- Networks
- Agents
- Interaction
- Aggregation
- Disaggregation
- Emergence
- Complexity
- The Fractal Company (Book)
- The Fractal Organization (Book)
- Viable Systems Model (Stafford Beer)
- Self Similarity
- Power Laws
From Multilevel Theory, Research, and Methods in Organizations
Foundations for Multilevel Theory in Organizations
Conceptual Underpinnings: General Systems Theory
General systems theory (GST) has been among the more dominant intellectual perspectives of the twentieth century and has been shaped by many contributors (e.g., Ashby, 1952; Boulding, 1956; Miller, 1978; von Bertalanffy, 1972). Systems concepts originate in the “holistic” Aristotelian worldview that the whole is greater than the sum of its parts, in contrast with “normal” science, which tends to be insular and reductionistic. The central goal of GST is to establish principles that generalize across phenomena and disciplines-an ambitious effort that is aimed at nothing less than promoting the unity of science.
Systems principles are manifest as analogies or logical homologies. Logical homologies represent identical concepts (that is, isomorphism), and parallel processes linking different concepts (that is, homology), that generalize to very different systems phenomena (von Bertalanffy, 1972). For example, it is noted that open systems counteract the second law of thermodynamics-entropy-by importing energy and information from the external environment, and transforming it, to maintain homeostasis.
Feedback and servo- mechanisms are the basis for the purposive responses of cybernetic systems. Organizational systems are proposed to have analogous structures and processes (e.g., Katz & Kahn, 1966; Miller, 1978).
Whether one takes a more macro (Parsons, 1956, 1960) or micro (Allport, 1954) perspective, the influence of GST on organizational science has been pervasive. Unfortunately, however, that influence has been primarily metaphorical. The bureaucratic-closed systems-machine metaphor is contrasted with a contingent-open systems-living organism metaphor. Although metaphor has important value-virtually all formal theory is rooted in underlying metaphor (Morgan, 1983)-lack of specificity, formal identity, and precise definition can yield truisms that mislead and fail the test of science (Pinder & Bourgeois, 1982; Bourgeois & Pinder, 1983). GST has exhibited heuristic value but has contributed relatively little to the development of testable principles in the organizational sciences (Roberts et al., 1978). It is to this latter concern that the multilevel perspective is directed.
As social systems, organizations are qualitatively distinct from living cells and other concrete physical systems. The goal of the multilevel perspective is not to identify principles that generalize to other types of systems. Although laudable, such an effort must often of necessity gloss over differences between qualitatively different systems in order to maintain homology across systems (compare Miller, 1978). The primary goal of the multilevel perspective in organizational science is to identify principles that enable a more integrated understanding of phenomena that unfold across levels in organizations.
Macro and Micro Perspectives
Fundamental to the levels perspective is the recognition that micro phenomena are embedded in macro contexts and that macro phenomena often emerge through the interaction and dynamics of lower-level elements. Organizational scholars, however, have tended to emphasize either a micro or a macro perspective. The macro perspective is rooted in its sociological origins. It assumes that there are substantial regularities in social behavior that transcend the apparent differences among social actors. Given a particular set of situational constraints and demographics, people will behave similarly. Therefore, it is possible to focus on aggregate or collective responses and to ignore individual variation. In contrast, the micro perspective is rooted in psychological origins. It assumes that there are variations in individual behavior, and that a focus on aggregates will mask important individual differences that are meaningful in their own right. Its focus is on variations among individual characteristics that affect individual reactions.
Neither single-level perspective can adequately account for organizational behavior. The macro perspective neglects the means by which individual behavior, perceptions, affect, and interactions give rise to higher-level phenomena. There is a danger of superficiality and triviality inherent in anthropomorphization. Organizations do not behave; people do. In contrast, the micro perspective has been guilty of neglecting contextual factors that can significantly constrain the effects of individual differences that lead to collective responses, which ultimately constitute macro phenomena (House et al., 1995; Klein et al., 1994; Roberts et al., 1978; Rousseau, 1985).
Macro researchers tend to deal with global measures or data aggregates that are actual or theoretical representations of lower-level phenomena, but they cannot generalize to those lower levels without committing errors of misspecification. This renders problematic the drawing of meaningful policy or application implications from the findings. For example, assume that we can demonstrate a significant relationship between organizational investments in training and organizational performance. The intuitive generalization-that one could use the magnitude of the aggregate relationship to predict how individual performance would increase as a function of increased organizational investments in training-is not supportable, because of the well-known problem of ecological inference. Relationships among aggregate data tend to be higher than corresponding relationships among individual data elements (Robinson, 1950; Thorndike, 1939). This fact continues to be a significant difficulty for macro-oriented policy disciplines-sociology, political science, economics, education policy, epidemiology-that attempt to draw individual-level inferences from aggregate data.
Micro researchers suffer from an obverse problem, which also makes the desire to influence human resource management policy difficult. We may, for example, be able to show that individual cognitive ability increases individual performance. However, we cannot then assert that selection systems that produce higher aggregate cognitive ability will necessarily yield improved organizational performance. Perhaps they will, but that inference is not directly supported by individual-level analyses. Misspecifications of this sort, however, are not unusual (Schmidt, Hunter, McKenzie, & Muldrow, 1979). Such “atomistic fallacies,” in which organizational psychologists suggest team- or organization-level interventions based on individual-level data, are common in our literature.
A levels approach, combining micro and macro perspectives, engenders a more integrated science of organizations. House and colleagues (1995) suggest the term meso because it captures this sense that organizational science is both macro and micro. Whatever it is called, we need a more integrated approach. The limitations that the organizational disciplines suffer with respect to influencing policy and applications can be resolved through the development of more complete models of organizational phenomena-models that are system-oriented but do not try to capture the complexity of the entire system. Instead, by focusing on significant and salient phenomena, conceptualizing and assessing at multiple levels, and exhibiting concern about both top down and bottom-up processes, it is possible to build a science of organizations that is theoretically rich and application-relevant.
Please see my related posts:
Boundary Spanning in Multinational and Transnational Corporations
Hierarchy Theory in Biology, Ecology and Evolution
Hierarchical Planning: Integration of Strategy, Planning, Scheduling, and Execution
Boundaries and Relational Sociology
Micro Motives, Macro Behavior: Agent Based Modeling in Economics
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