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The ultimate deﬁnition of organizational size is the sum total of social resources the organization has acquired from its environment. These resources include knowledge, power, wealth, people, and legitimation. Early in the history of the science of organizations, size usually meant the number of people employed. This no longer suffices, as will be shown.
Size has been one of the most commonly used variables in organization studies. Intuitively, size is easy to grasp and it is easy to consider its inﬂuence upon organizational behavior. Debates about the role of size have contributed to the development of organization studies as a scientiﬁc discipline.
It was Weber who stimulated empirical studies of organizations, especially after 1946, when an English translation of some of his work appeared as From Max Weber: Essays in Sociology (Weber 1949). Early studies were case studies and focused on a single organization or a part of an organization at a time (e.g., Selznick 1949, Gouldner 1954, Blau 1955); hence, size was outside of their concerns. But size did become a major focus after comparative studies came into being, and once a common framework and a set of instruments for measuring organizational variables had been created. Studies of multiple organizations, or comparative studies, found much variation in organization structure, begging the question of why, and what, is responsible for the variation.
Three camps emerged. One emphasized size purely on empirical grounds, the second suggested technology partly for ideological preference, and the third, culture, speculation, and romanticism.
Size as a possible determinant of structure is easy to understand. Structure is plausibly a function of how many people work in an organization. Division of labor must presume the presence of a certain minimum number of persons, or there could be no division of labor. Hierarchy of authority or centralization, too, must assume there are enough people to have a hierarchy. The same is true of such other structural variables as formalization and stratiﬁcation.
The emergence of the technology camp is best understood within the political context of a resurgence of Marx in the 1960s in academia in North America. One of the important notions of Marx was worker alienation enhanced by increasing technological sophistication, and bureaucratization in modern society. Blauner (1964) tested this idea with North American data and argued that worker alienation varied by the type of technology used by the industrial organization. The implication was that technology affected worker alienation through the medium of organization structure; hence, technology is an important determinant of structure. Another study, quite independent of Blauner, demonstrated that the type of technology used by the organization called for its own appropriate structure, and when it deviates from the appropriate structure, the organization proves to be unsuccessful (Woodward 1965). Fanning the popularity of the technology camp, Perrow (1967) gave it some theoretical rationale, suggesting that the variability of the raw materials to be processed by the organization dictated the type of technology to be utilized, hence the organization structure.
The culture camp had its semistart in the work of Abegglen (1958) which suggested that in non-Western societies there could be other ways of organizing business concerns than was thought appropriate in the West. Crozier (1964) gave this camp a boost when he attempted his cultural analysis of the French organizations he had studied and analyzed. He said that those who were in the organizations he studied were French, hence carriers of French culture, with its own ‘permanent French culture traits.’ The culture which organization members bring into the organization would shape its structure and would help in understanding its behavior. Meyer and Rowan (1977), and more directly Hofstede (1980), called for attention to culture in organization studies. The emphasis of the culture camp, however, was on values of people and did not include either organizational size or technology. Some work arising out of this camp appears to deny the possibility of the science of organizations (Osigweh 1989).
The most commonly used indicator of organizational size has been the number of employees of the organization. Early work predating the size vs. technology controversy but using size as an independent variable attempted to predict the administrative ratio, or the percentage of personnel doing administrative work. A simple model depicting a positive effect of personnel size on administrative ratio was conﬁrmed with school district data from California (Terrien and Mills 1956). Anderson and Warkov (1961) added complexity as another independent variable when the above model was not supported by their data from Veterans Administration hospitals in the USA. Later studies conﬁrmed a positive effect of complexity and a negative effect of size on administrative ratio. The negative effect of size on percentage administrative personnel has been shown in studies of the optimal supervisory ratio when the tasks of persons to be supervised are similar, and the number of persons the supervisor can supervise effectively comes down when their tasks are varied and require expert skills and knowledge (Woodward 1965).
Studies on the relationship of size with structural variables have shown interesting results. While Weber was thought to have expected positive relationships among hierarchy of authority, system of rules and procedures, and division of labor (Hall 1963), and Hage (1980) depicts, in his axiomatic theory, centralization and formalization as being associated positively with each other, empirical studies have shown inconsistent results in the relationship among structural variables and size. Hage uses complexity instead of Hall’s division of labor or Aston’s specialization, and his complexity is qualitatively different from division of labor and specialization. Complexity includes elements of knowledge and qualiﬁcations, and is expected to be associated negatively with centralization and formalization.
Aston’s studies found a positive effect of size to specialization and formalization, and a negative one to centralization. Blau and Schoenherr (1971) reported similar results. A replication of the Aston study with 50 factories in Japan found similar results (Azumi et al. 1979). Consistent with these results, centralization has been found to be associated negatively with formalization. This led Blau and Schoenherr to speculate that centralization and formalization are alternative ways of control in which more formalization permits delegation of authority to lower levels. A more recent study of a nationally representative sample of organizations (Kalleberg et al. 1996) reports negative relations of size and bureaucratization, and size and centralization, and positive relations between size, differentiation, and formalization.
Those who are most commonly identiﬁed with the size camp were the Aston group (Pugh et al. 1969, Hickson et al. 1969) and Blau (1970) and his associates, who used the number of fulltime employees as an indicator of size. For the Aston group, size is one of their ‘contextual’ variables, or social resources, that are drawn in from the environment to the organization. Some have used the number of participants in the organization as an indicator of size, raising the issue of organizational boundaries, where some would include students as part of organization size, while others would exclude them as clients.
Kimberly (1976) suggested that there are four components to size: physical capacity (e.g., plant capacity, number of beds in a hospital, etc.); number of personnel; organizational inputs or outputs; and discretionary resources available (e.g., assets, wealth, university endowment). Before the appearance of the Kimberly article, most empirical studies of organizations had used personnel size as indicator of size.
The Aston group were unable to replicate the Woodward study: They found that the inﬂuence of technology was limited to workﬂow. One of the more consistent ﬁndings after Aston has been the positive relationship between size and what they called ‘structuring of activities,’ especially specialization. Blau (1970) created a ‘formal theory’ linking structural differentiation, administrative economy, and overheads. Increasing size is the cause of differentiation in this scheme, and differentiation has two faces: On the one hand it creates subunits in each of which people tend to do similar tasks, hence requiring relatively few supervisors; and on the other hand, the subunits created tend to engage in different tasks, which requires more supervisors or coordinators. Thus, differentiation promotes intra-unit similarity and inter-unit diversity. The former reduces administrative cost, while the latter increases it and feeds back negatively on the differentiation process.
The issue of size vs. technology has declined in importance as some researchers have moved to combine elements of both to come up with new variables such as task scope (Hage 1980) and scale (Azumi et a 1983).
Some of the major criticism of the size camp came from Argyris (1972), who questioned whether in-creasing size actually causes differentiation, and Aldrich (1972a and 1972b), who suggested that size is a dependent variable of structure. One lesson that has been learned from the size vs. technology controversy is that any attempt to ﬁnd one determinant of structure is likely to fail.
So what has become of organizational size as a variable for organization science? The issues surrounding structure, its variety, what may determine it, and its effects on organizational processes and performances have continued to evolve. Organizational size continues to be a commonly used variable, but it no longer has the passionate focus it once had.
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