One theory holds that in the early stages of development, organizations allocate as .... School districts provide nonteaching services like lunch programs, adult.
Academy of Management Journal 1978, Vol. 21, No. 1, 6.-22
System Influence on Organizational Decision Making: The Case of Resource Allocation^ RICHARD L. DAFT Queen's University This paper reports the relationship of three organization contextual variables—size, affluence and employee education—to resource allocation in 91 not-for-profit school organizations. The contextual variables are significantly related to resource allocation. The major relationship is with the allocation of resources between core functions and overhead functions: Overhead functions receive a larger share of resources in both large and affluent school organizations. All organizations are faced with the task of allocating scarce economic resources among departments. Most managers and most students of organizations would agree that decisions about budgets, expenditures, salary levels, and other resource allocation matters occupy a substantial place in the activities of organization participants. But despite the apparent importance of these activities, there has been little attention paid to resource allocation processes in the empirical literature on organizational behavior and management (Pondy, 1970). There are at least two views concerning the allocation of organizational resources. One view suggests that objective criteria dominate the decision process. Baldridge (1971) calls this the bureaucratic model of organization decision making. Organizational subunits are expected to receive uniform treatment, and resources are allocated according to universalistic criteria such as respective workload and the relative contribution to company goals. The second view argues that objective criteria do not explain organizational decision making (Baldridge, 1971; Cyert & March, 1963). Political factors distort the objective, computational decision process. Richard L. Daft is Assistant Professor, School of Business, Queen's University, Kingston, Ontario. 1 This research was supported by the Center for the Management of Public and Nonprofit Enterprise, Graduate School of Business, University of Chicago, and the School of Business, Queen's University at Kingston, Ontario. Norman Macintosh and William Cooper made several helpful comments on earlier drafts of this paper.
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Organizational goals and decision criteria may be ill-defined; consequently, resource allocation decisions result from discussion, bargaining and compromise among organization groups. The influence and political activities of subgroups thus substantially influence resource allocation outcomes. Recent research provides empirical evidence for the relationship between political processes and resource allocation. Pfeffer and Salancik (1974) undertook to explain the percentage of total resources allocated to each of the 29 departments at a major university. The focus of their investigation was on power relationships and political processes, and they found that department power was related to the proportion of resources received by each department. Powerful departments were able to secure resources above what would be expected on the basis of departmental work load, number of faculty, and reputation. The purpose of this paper is to build upon the work of Baldridge (1971) and Pfeffer and Salancik (1974) by empirically investigating a third type of influence on resource allocation. It is argued here that organization contextual variables influence resource allocation decisions. Variables such as organization size, technology, goals, the nature of the environment, or even the amount of available resources impose upon decision makers specific requirements or constraints that influence resource allocation decisions in a predictable manner. Resource allocation decisions are assumed to be the result of a complex set of organizational influences. Objective factors and power relationships each have a definite role, but so do organization structure and environment. This paper concentrates on the effects of the previously unexplored variables which represent the larger context within which resource allocation decisions are made. The analysis will examine the deployment of resources among several organization functions, but particular emphasis will be given allocation between so-called overhead functions and the functions that represent the technical core (Thompson, 1967) of the organization. Overhead functions are those that support the organization itself and whose services are consumed within the organization. Core functions represent the primary purpose of the organization. Core departments typically provide services or products for consumption by the organization's clients. The study also deals with the effects of two contextual variables that have practical importance for not-for-profit organizations—organization size and organization revenues. Size and revenues have practical implications because not-for-profit organizations typically serve fixed commutiity domains, and these domains differ widely in the size of the population served and in the local financial support. The resulting differences in organization size and affluence raise the issue for policymakers of whether the domain boundaries should be changed in the interest of either organizational efficiency or public equity. It is occasionally argued, for example, that consolidating public organizations at the county, state or even the federal
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Academy of Management Journal
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level will provide services more efficiently; consolidation creates one large organization to deliver services to recipients in a large domain. Revenues are a policy consideration also because organizations in wealthy communities are usually able to provide more services to the public; the policy alternative is to take over financing at a central level and provide the same dollars per capita to each organization of a given type. The research reported here will indicate how resources are deployed under different conditions of organization size and affluence. In addition to the variables of organization size and affluence, the study will evaluate the impact of the educational level of organization employees. This variable is included because large and wealthy not-for-profit organizations are able to obtain highly qualified technical personnel, who in turn may use their influence to obtain a larger share of available resources. By measuring employee education, it will be possible to ascertain whether any observable effect of organization size or affluence is the result of the contextual variables or the result of the type of personnel these organizations attract. CONTEXTUAL VARIABLES AND RESOURCE ALLOCATION Organization Size There is evidence in the literature that large organizations are intrinsically different from small ones, even when the organizations have similar goals and technologies. Large organizations are bureaucratized and employ greater use of rules and procedures than small organizations (Hall, 1972; Pugh, Hickson, Hinings & Turner, 1969). Large organizations also tend to have larger spans of control and to have a larger number of both vertical levels and horizontal divisions (Hall, 1972; Meyer, 1968). The complexity and bureaucratic characteristics of large organizations can be expected to have two influences on resource allocation. First, rules, procedures and other formal communications are important sources of coordination and control. Consequently, those groups responsible for the formal paperwork systems will have to be proportionately bigger and receive proportionately more resources in large organizations. Evidence of the greater requirement for formalized communications in large organizations is the positive relationship between the clerical ratio and size reported by Rushing (1967), James (1972) and Kasarda (1974). Second, large organization size can have the opposite effect on administrative personnel. Administrators frequently comprise a smaller proportion of personnel in large organizations (Blau, 1972; Anderson & Warkov, 1961; Pondy, 1969; Rushing, 1967; Indik, 1964; Haas, Hall & Johnson, 1963). The explanation for smaller administrative ratios is that large organizations utilize rules, larger spans of control, impersonal
1978
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communication, and other devices in place of personal supervision.^ In large organizations the administrative savings can be allocated to other overhead functions, such as clerical, or to the technical core which provides services to the public. There are typically several functions in addition to clerical and administration in not-for-profit organizations, biit the deployment of resources to these functions has not been widely studied. Child (1972) concluded that the maintenance component increased at about the same rate as organization size. There is some evidence that professional staff personnel, who are hired to provide nontypical services to the community, become somewhat more important in large school organizations (Holdaway & Blowers, 1971; Kasarda, 1973). Public organizations that serve large, heterogeneous communities probably face a demand for a wide variety of services. A somewhat greater proportion of resources may have to be devoted to staif functions that augment the core services in large organizations. There is no research in the literature that reports the proportion of resources allocated to the technical core of organizations. Most studies are concerned only with administrative or clerical personnel. Based on these studies, it is frequently argued that large organizations are more efficient because a smaller proportion of administrators is required (Blau, 1972). If the efficiency argument is correct, one would expect the technical core and related staff departments to receive a larger share of available resources. Administrative and other overhead departments would require and receive a smaller share of available resources. If this is found to be the case, then policymakers would be supported in their attempts to consolidate public organizations. The general hypothesis to be tested concerning organization size is as follows: Hypothesis 1—Large organizations allocate a larger proportion of resources to the technical core (as opposed to overhead departments) than small organizations. Organization Revenues
There is considerable evidence that not-for-profit organizations function under widely varying financial circumstances (Klatsky, 1970; Guthrie, Kleindorfer, Levin, & Stout, 1971). Not-for-profit organizations with high per capita revenues often provide more and better services to their constituencies (Guthrie et al., 1971). But exactly how are revenues used in affiuent organizations? Do incremental revenues go into services for the public or into administration? There has been virtually no empirical research into the effect of affiuence on the deployment of resources. 2 Freeman and Kronenfeld (1973) argue that another explanation for these findings is definitional dependency between organization size (S) and the administrative ratio (A/S), because S is the major component of each variable. MacMillan (1975), however, identifies problems in the Freeman and Kronenfeld paper and argues that the zero-order correlation of S with A/S yields valid findings.
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Academy of Management Journal
March
One theory holds that in the early stages of development, organizations allocate as many of their resources as possible to carry out core activities and satisfy organization clients (Becker & Daft, 1976). If organizations successfully deal with clients, revenues tend to increase and organizations are then able to allocate resources to noncore activities. The departments which benefit from affluence will be staff departments which supplement core activities and which provide support (clerical, maintenance) to the organization itself. When revenues are severely restricted, the technical core will receive a larger proportion of resources because the technical core reflects the primary goal of the organization. Opposing arguments are that some minimum amount of administrative and overhead machinery is required in each organization and that administrative decision makers provide for themselves even if resources are hmited. Thus administrative and other overhead departments will receive a larger share when revenues are scarce. When abundant revenues are available, a larger share can be allocated to core departments. Without empirical evidence it is not possible to say how revenues affect resource allocation. The initial emphasis of organization decision makers probably will be on core activities, so the proportion of resources allocated to the technical core will be largest when revenues are small. In organizations with greater resources, a larger share can be allocated to noncore activities. Hypothesis 2—Organizations with large per capita revenues allocate a smaller proportion of resources to the technical core than organizations with small per capita revenues. Employee Education When the educational level of employees in a department is high, the percentage of resources allocated to that department also can be expected to be high. Highly qualified employees receive higher salaries. Highly educated employees tend to be professional, which means they tend to be autonomous, mobile, and to have internalized standards of performance (Hall, 1972). These employees can be expected to push for additional resources, and the organization may have to acquiesce or risk losing them. Departments comprised of highly educated employees will tend to bid scarce resources away from other departments in the organization. To some extent, employee education represents power relationships in the organization. When there are educational differences among departments, then resource allocation may reflect the relative power and influence of each department. The technical core is the largest single function in most not-for-profit organizations. The educational level of personnel in the technical core will determine in part the share of resources allocated to the technical core.
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Hypothesis 3—When employees in the technical core are highly educated, the organization will allocate a larger proportion of resources to the technical core. METHOD The sample of not-for-profit organizations for this study is 91 public high school districts in Illinois. All four-year high school districts with more than 500 students are included in the sample. The unit of analysis is the school district, not the high school. The district is the appropriate unit of analysis because resource allocation is a district level phenomenon. The school district is the legal organization unit in Illinois. Revenues are collected and spent for the entire district rather than for individual schools. Each district has local taxing power and 71 percent of revenues come from the local community. The remainder comes from state and federal sources. The technology of each school district is similar because each district in the sample is organized to provide only grades 9-12 education. Some Illinois school districts also provide primary or junior college education. Those districts were excluded from the sample because the goals, technology, and financing arrangements for districts providing different levels of education are not comparable. Each school district files an annual financial statement with the office of the Illinois Superintendent of Public Instruction. The salaries expended for each major activity in the district are reported on thefinancialstatement. Nonsalary expenditures for items such as equipment and supplies are also reported in the financial statement, but these expenditures are reported in the aggregate. It was not possible to determine which department spent the nonsalary items. Hence the allocation of salary expenditures will be used as the measure of resource allocation in each district. Manpower accounts for the large majority of expenditures in each district (80.1 percent). It is assumed that departmental consumption of other items, such as supplies and equipment, will tend to reflect the size of the department. Salary allocation, which represents the relative size of departments, is expected to be highly correlated with total resource allocation. The primary function of high schools is classroom teaching, so resources devoted to that activity are considered allocated to the technical core. Within the technical core, school districts typically do not have clearly defined departments. Large districts may use part-time department heads to coordinate matters in each subject matter area. Teachers typically report to a principal or superintendent because part-time department heads do not have line authority. Hence, the teaching function will be treated as a single function in the district. School districts provide nonteaching services like lunch programs, adult education, guidance counseling, speech therapy, athletics, health, and special education. Some of these services closely support classroom teaching while others do not, so they will be divided into two groups: (1) auxiliary
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Academy of Management Journal
March
educational services that support classroom teaching, and (2) other student and community services. Employees in these groups do not teach, but they do provide services to the public. There are three functions in the school district which are considered overhead—administrative, clerical, and maintenance. The administrative function involves supervision and coordination within the school district. The clerical function includes all of the clerical and secretarial support for teachers and administrators. The maintenance function includes the personnel who handle the operation and maintenance of buildings, equipment and grounds. The analysis of resource allocation is similar to the procedure used by Pfeffer and Salancik (1974). The dependent variable is the allocation of the budget. The relative allocation to a given department is measured by the percentage of resources received by the department. It should be emphasized that the analysis concerns the percentage of resources allocated to each department and not the absolute dollar amount. The specific salary expenditures which are included in each of the six major functions in the high school districts are listed below. The data are for the 1970-71 school year. Teaching—Proportion of total salaries paid to classroom teachers. Auxiliary Educational Services—Proportion of total salaries paid to provide services to students in support of classroom education. This category includes guidance and psychological counseling, librarians, health, teacher aids, and audio-visual. Other Student and Community Services—^Proportion of total salaries paid to personnel involved in other student and community programs, which include adult education, summer school, lunch, athletics, manpower development and training, and economic opportunity project. Administration—Proportion of total salaries paid to individuals involved in the administrative function, which include superintendents, principals, their assistants, supervisors, coordinators, business managers, and other administrative staff. Clerical Support—Proportion of total salaries paid to secretaries, clerks, and personnel who monitor attendance and textbooks. Operations and Maintenance—Proportion of total salaries paid to personnel involved in the operation and maintenance of buildings, equipment, grounds, and transportation. The contextual variables to be studied are organization size, organizational affluence, and teacher education. School districts are part of the local community and are subject to contextual influences along a variety of social and economic dimensions. Many of these influences, however, will be felt through the current size, revenues, and teacher education observed in the district. District size reflects urban versus rural context. Total revenues reflect community wealth. Teacher education reflects both community wealth and community socio-economic status (Daft & Becker, in press).
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Hence the immediate impact of several social and economic dimensions on the allocation of resources is represented by size, revenues, and teacher education. Size of the school district is measured as the number of students. Number of students is frequently used in studies of educational organizations and represents the demands placed upon such organizations by the community. Number of students usually is positively correlated with other measures of organization size. In this sample of high school districts, number of students is correlated .9 with number of teachers. Revenues per pupil are the measure of district aflluence. Revenues per pupil control for the size of the district and indicate whether the relative size of the total resource pie is larger or smaller than other districts. Educational level of employees in the technical core is measured as the percentage of teachers in the district who have a master's degree. Means and standard deviations for all variables are shown in Table 1. TABLE 1 Means and Standard Deviations for each Variable (n = 91) Variable Teaching Auxiliary Educational Services Other Services Administration Clerical Maintenance Total Salary Size Affluence Education«
Mean
Staridard Deviation
Percent of Total Salaries
$1,793,985 162,801 132,049 223,637 102,748 255,656 $2,670,876 2,894 $996 .49
$1,913,230 246,364 162,820 295,861 138,716 302,310 $2,940,366 2,767 $182 .13
67.2 6.1 4.9 8.4 3.9 9.6 100.0
Percentage with master's degrees
RESULTS
The intercorrelation matrix for the variables in the study is in Table 2. The proportion of resources allocated to teaching has a negative relationship with the proportion of resources allocated to each of the other departments (first row in Table 2). These correlations are evidence for the zero-sum nature of resource allocation decisions. In order to increase resources to the teaching component, which is the largest component, the resources to other components have to be decreased, and vice-versa. The proportion of resources allocated to teaching is negatively associated with the three contextual variables of size (r = —.36), aflluence (r = —.32), and teacher education (r = - . 2 4 ) . The data in Table 2 also indicate that the contextual variables have significant positive correlations with each other (r = .47, .45, .58). To isolate the independent relationship of each contextual variable with the allocation of resources, it will be necessary to control for the other two.
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1978
Daft
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TABLE 3 Partial Correlations of Size with Proportional ADocation of Resources, Controlling for Affluence and Teacher Education _ Resources Administration Clerical Maintenance Teaching Auxiliary Education Services Administration, Clerical and Maintenance
stze .00 .26 .21 .24 .16 .01 .24
Significance (one-tail) .01 .03 .01 .06 .01
Partial correlation analysis is ideally suited to identify the effect of each organization contextual variable on resource allocation. The partial correlations between organization size and the proportion of resources allocated to each component, controlling for affluence and teacher education, are in Table 3. The Table 3 coefficients indicate that size has a statistically significant relationship with resource allocation. In the large districts, proportionately more resources go to clerical (r = .26), maintenance (r = .21) and auxiliary educational services for students (r = .16). The positive relationship of size with clerical ratio is compatible with previous research (Rushing, 1967; James, 1972; Kasarda, 1974) and supports the interpretation that large organizations have proportionately greater internal requirements for written and formalized communication activities. The relationship between size and maintenance indicates that large organizations also have proportionately greater requirements for the operation and maintenance of equipment, buildings, and grounds. The relationship of size with auxiliary educational services is only modestly significant, but suggests that large districts experience somewhat greater needs for educational services to supplement classroom teaching. Supplementary education is probably a function of the heterogeneous student population in the larger school districts. There are sufficient numbers of students who need counseling, etc. to justify hiring specialists. The technical core of the school district—classroom teaching—receives a smaller share of the resources in the larger school districts (r = —.24). Bidwell and Kasarda (1975) observed that large high school districts had larger student/teacher ratios than small districts. The number of teachers and the amount of resources allocated to the teaching component do not seem to keep pace with the number of students. There are three possible explanations for the proportionately smaller size of the teaching component in large districts. One explanation is that large districts simply need proportionately larger clerical, maintenance, and auxiliary educational services components. The importance of these departments forces some reallocation of resources away from teaching to support these functions. Another explanation is that large districts may
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Academy of Management Journal
March
experience certain economies of scale in teaching. Teachers can be specialized, perhaps classes can be larger, and some of the nonteaching activities such as taking attendance or duplicating material may be taken over by other functions. Another possible explanation is higher salary levels in urban (large districts) as opposed to rural (small districts) areas. Maintenance, for instance, may be unionized in urban areas and demand a disproportionately large share of the salaries. Salary levels may be higher in urban areas, but this probably does not explain the allocation of resources from one department to another. Teachers also tend to be unionized in urban areas, and clerical and other functions also receive higher salaries than their counterparts in rural communities. To probe the effect of size further, the resources allocated to clerical, maintenance and administration are combined. The proportion of resources allocated to all of these departments indicates the relative cost of all overhead activities in the district. The partial correlation between total overhead and size is in Table 3. The overhead functions receive a proportionately larger share of the resources in the large districts (r = .24). (The proportion of resources allocated to educational functions—teaching, auxiliary education, other services—is the inverse of the proportion allocated to overhead, and the coefficient between size and the combined educational functions is the same except for the sign, r = —.24). The data do not support the notion that large districts are administratively more efficient than small districts. The first hypothesis is not supported. On the contrary, large organizations allocate proportionately more resources to overhead departments at the expense of the technical core. Hypothesis two concerns the effect of district affiuence on resource allocation. Does the relative size of the resource pie to be divided among organization subgroups influence the deployment of resources? The data in Table 4 indicate that it does, and in a fashion similar to size. Affiuence has a statistically significant relationship with the proportion of resources allocated to clerical (r = .20), maintenance (r = .27) and teaching (r = —.15). As additional resources are made available to a school district, controlling for size and education, the clerical and maintenance groups receive a larger share, and teaching receives a reduced share of those resources. What is probably happening is that poOr districts strive to reach a minimum level of teaching services. In districts with more than minimum revenues, dollars are used to obtain support for teachers and administrators. Support personnel can do tasks which teachers and administrators prefer to avoid and which may make them more efficient. Moreover, when dollars are available, equipment and other facilities can be obtained so that additional maintenance personnel are needed to service and operate this equipment. . It is interesting to note, however, that greater revenue in a district is not related to proportionately more resources in nonteaching educational services, such as counseling and athletics. Notie of the education related
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TABLE 4 Partial Correlations of Affluence with Proportional Allocation of Resources, Controlling for Size and Teacher Education Resources to Administration Clerical Maintenance Teaching Auxiliary Education Services Administration, Clerical and Maintenance
Per Capita Revenues .03 .20 .27 -.15 -.02 .09 .26
Significance (one-tail) .03 .01 .08 .01
functions benefit disproportionately as a result of greater revenues, only overhead functions do. The data in Table 4 also indicate that when overhead functions are aggregated ,they receive a larger share of resources in the wealthy districts (r = .26). Resource allocation decisions under conditions of poverty tend to be different from decisions made under conditions of luxury. The districts with abundant dollars allocate a larger proportion of resources to overhead support. Hypothesis two, that large organizations allocate a smaller proportion of resources to the technical core, is supported. The third hypothesis concerns whether the presence of highly educated teachers will be associated with a larger share of resources for teachers. The relationship between teacher education and the proportion of resources that go to teaching is r = — .01 (Table 5). The educational level of teachers apparently offers no special leverage for obtaining resources. But teacher education is related to the share of resources going to administration (r = —.17). The negative relationship with administration may mean that teachers are able to bid resources away from administrators. A more plausible explanation is that fewer administrators are necessary or desirable for supervision when teachers are highly educated (Kasarda, 1973). Thus the presence of these highly educated teachers enables dollars to be spent on activities other than supervision. TABLE 5 Partial Correlations of Teacher Education with Proportional Allocation of Resources, Controlling for Size and Affluence Resources to Administration Clerical Maintenance Teaching Auxiliary Education Services Administration, Clerical and Maintenance
Teacher Education -.17 — .05 .25 -.01 .03 .03 .04
Significance (one-tail) .06 .01
—
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Academy of Management Journal
March
The positive relationship of teacher education with resource allocation to maintenance is unexpected (r = .25). Teachers might be expected to bid resources away from maintenance rather than adding to it. The positive relationship probably has to do with the support required for the highly educated teachers. Innovative techniques, programs and equipment tend to be used by highly educated teachers (Corwin, 1975; Daft & Becker, in press), which in turn require additional support from the operations and maintenance department. Thus teacher educational level is associated with resource allocation, but not with a larger allocation to teachers themselves. Hypothesis three is not supported. The data in Tables 3, 4 and 5 provide evidence that organizational contextual variables indeed influence internal resource allocation decisions. This infiuence is especially noticeable for the deployment of resources between functions classified as overhead and functions which deliver services directly to the public. It is possible to describe the exact impact of the contextual variables on resource allocation by fitting a regression equation to the data. These relationships are reported in the regression equation below: Y(IOO) = 86.81 + .00035Xi + .00641X2 + 1.333Xs (R = .46) (2.4) (2.5) (0.4) where Y = the proportion of resources allocated to overhead functions (administration, clerical, maintenance), Xi = number of students (size), X2 = revenues per student (affiuence), and X3 = percentage of teachers with masters degree. The /-values are in parentheses and are significant at the .01 level for size and affiuence. The regression equation indicates that the proportion of total resources allocated to overhead functions is 1 percent larger (and resources allocated to educational functions 1 percent smaller), for each increase in size across districts of 2,860 students. There are approximately 18 students per teacher in these districts, which means that for each 159 additional teachers, 1 percent of the resources changes from education to overhead. One percent of the resources also changes from education to overhead functions for each $156 increase in per pupil revenues across districts. These districts vary in size from approximately 500 to 16,500 students, and they vary from $650 to $1,550 in revenues per student. Consequently over 10 percent more of total salaries go to noneducational functions in large, wealthy districts compared to small, poor districts. This can translate into a substantial number of dollars deployed from education to overhead because the average salary budget in these districts in 1970-71 was $2,671,000, and the budget of the largest district was $13,500,000. DISCUSSION AND IMPLICATIONS
The abovefindingswere characterized by several statistically significant relationships. Organization size was associated with a greater proportion of
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resources allocated to clerical, maintenance and auxiliary educational services for students. Organization size was also associated with a smaller proportion of resources allocated to teaching. Organizational affluence was associated with a larger share of resources allocated to clerical and maintenance and with a smaller proportion of resources allocated to teaching. The educational level of teachers was related to a larger share of resources to maintenance and a smaller share to administration. Organization size and organization affluence are both related to a greater proportion of resources allocated to the combined overhead functions in the school districts. The findings must be interpreted with caution. There are inherent limitations with cross-sectional data. The effect of size, revenues, and educational level on resource allocation has been assessed by comparing across school districts. The study has not demonstrated that changes in size or revenues over time in a single district will have the same outcomes. It can only be inferred that this will happen. Moreover, the data only pertain to the proportional allocation of resources. Affluent districts spend more resources on educational functions than poor districts. It is the percentage of resources allocated to educational functions that is smaller. Caution also must be exercised in the generalization of the findings. Public high school districts obviously are not representative of all organizations. They do, however, share certain characteristics with other public and not-for-profit organizations. School districts are legal organizational entities and are financed with public funds. Public school districts serve relatively fixed geographical domains; there are large differences in the size and wealth of these domains; and the districts face little competition in the delivery of services to the community. Finally, revenues do not arise from a direct exchange with the consumer. Revenues come from third party sources (parents and other community residents). If the findings are characteristic of school districts and similar organizations, they provide new insight into the conditions which influence resource allocation. The organizational context within which decision makers work, such as size and affluence, has a substantial relationship with resource allocation among departments. Models of resource allocation which stress intemal power and political processes represent only part of the story of resource allocation (Pfeffer & Salancik, 1974). The educational level of teachers partially represents the influence of teachers, but educational level was unrelated to the percentage of resources received by teachers |n the school districts. It is not likely that the clerical function receives a larger share of resources in certain settings, and that teaching receives proportionately less, because of the relative power of the two groups. Rather, district size and affluence seem to generate certain requirements or opportunities to which decision makers respond. A further interpretation of the data is that when organizations are in the early stages of development, when they are small and resources are
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Academy of Management Journal
March
scarce, the primary requirement facing the organization is delivery of its services. The technical core delivers services to the organization's clients, and this function receives first priority. When organizations are large, the requirements are different. The generation and maintenance of the paper work system is more important. The physical plant and facilities also need a larger share of resources. When revenues are available, a larger share is spent on these overhead functions. But organizations provide core services first, and only when they are large or have adequate revenues do organizations spend proportionately more resources on overhead departments. This utilization pattern supports the Becker and Daft (1976) theory of organizational development. The finding that large organizations have proportionately greater overhead costs is new to the empirical literature on organizations. Based on several studies, Blau (1972, p. 6) stated that: "Contrary to the stereotype of the proliferation of bureaucratic machinery in large organizations, the administrative apparatus is proportionately smaller in large than in small organizations." But earlier studies considered only administrative personnel. The total cost of the overhead machinery was understated because nonsupervisory overhead functions (clerical, maintenance) were not included. By examining resource deployment throughout the organization, the opposite result is found. Overhead costs are proportionately greater in large rather than small organizations. The impact of size and revenues has implications for public policy decisions regarding the delivery of public services. It is often proposed, especially in high school organizations, that districts be financed on a uniform per pupil basis (Guthrie et al., 1974). In this way inequities across districts in the provision of educational services supposedly will be removed. But the findings above suggest that uniform financing may not equalize educational services because large districts allocate proportionately more resources to overhead activities. Under uniform financing, a smaller percentage of the educational dollars will reach the classroom in large districts. Large districts would be hard pressed to meet requirements for overhead costs and for nonteaching services and still provide comparable resources to classroom teaching. The problem of financing public services in an equitable manner affects many types of public organizations. New alternatives, such as uniform financing of technical core activities and unequal financing of support activities, may offer a better solution than uniform financing on a per capita basis. Another implication of the above findings concerns the evaluation of performance in not-for-profit organizations. Typically, outputs of public organizations are difficult to define and measure. Hence there is a tendency to evaluate these organizations on the basis of input, or cost. But small organizations and poor organizations will appear to be more efficient on the basis of certain financial cost ratios. The overhead costs will be proportionately more in the large and affiuent organizations, but this may be be-
1978
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cause of legitimate requirements for clerical and maintenance services. The performance evaluation of large and small organizations, or rich and poor organizations, should allow for different requirements. These findings also have implications for top level administrators within not-for-profit organizations. The technical core should receive top priority, so if the organization is small and poor, every effort should be made to support this activity. But in large organizations, administrators should be prepared to invest in overhead activities. The large organizations have greater requirements for paper work, other written communications, and maintenance. These requirements appear to be legitimate, so administrators should not starve the overhead functions because of the belief that only the technical core does important work. Moreover, when revenues are available, organizations apparently invest proportionately more in overhead activities. Support activities may make technical core personnel more efficient. Finally, administrators should be cautious about comparing their performance to other organizations on the basis of cost ratios. Valid comparisons are most likely to be observed if the contextual variables are similar for each organization. More research obviously is needed into the allocation and utilization of resources in public organizations. Can the findings reported here be replicated in other types of organizations? How does allocation of resources relate to physical output? Many questions remain to be answered. If, for example, it can be determined whether the proportionately greater overhead costs associated with large size are related to proportional increases in output, then we can say more about how public organizations should be organized. It is possible that our public organizations would utilize resources more efficiently by delivering services with groups of small, specialized organizations rather than with large, consolidated ones. REFERENCES 1. Anderson, T. R., and S. Warkov. "Size and the Administrative Component in Occupational Associations," Pacific Sociological Review, Vol. 13 (1970), 241-251. 2. Baldridge, J. V. Power and Confiict in the University (New York: Wiley, 1971). 3. Becker, S. W., and R. L. Daft. "Toward a Theory of Organizational Development," (Unpublished manuscript. University of Chicago, 1976). 4. Bidwell, C. E., and J. D. Kasarda. "School District Organization and Student Achievement," American Sociological Review, Vol. 40 (1975), 55-70. 5. Blau, P. M. "A Formal Theory of Differentiation in Organizations," American Sociological Review, Vol. 35 (1970), 201-218. 6. Blau, P. M. "Interdependence and Hierarchy in Organizations," Social Science Research, Vol. 1 (1972), 1-24. 7. Child, J. "Parkinson's Progress: Accounting for the Number of Specialists in Organizations," Administrative Science Quarterly, Vol. 18 (1973), 328-348. 8. Corwin, R. G. "Innovation in Organizations: The Case of Schools," Sociology of Education, Vol. 48 (1975), 1-37. 9. Cyert, R. M., and J. G. March. A Behavioral Theory of the Firm (Englewood Cliffs NJ.: Prentice-Hall, 1963). 10. Daft, R. L., and S. W. Becker. The Innovative Organization (New York: Elsevier, in press).
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11. Freeman, J. H., and J. E. Kronenfield, "Problems of Definitional Dependency: The Case of Administrative Intensity," Social Forces, Vol. 52 (1973), 108-121. 12. Guthrie, J. W., G. B. Kleindorfer, H. M. Levin and R. T. Stout. Schools and Inequality (Cambridge: MIT Press, 1971). 13. Haas, E., R. H. Hall and N. J. Johnson. 'The Size of the Supportive Component in Organizations: A Multi-Organizational Analysis," Social Forces, Vol. 42 (1963), 9-17. 14. Hall, R. H. Organizations: Structure and Process (Englewood Cliffs, N.J.: PrenticeHall, 1972). 15. Holdaway, E. A., and T. A. Blowers. "Administrative Ratios and Organization Size: A Longitudinal Examination," American Sociological Review, Vol. 36 (1971), 278-286. 16. Indik, B. P. "The Relationship Between Organization Size and the Supervision Ratio," Administrative Science Quarterly, Vol. 9 (1964), 301-312. 17. James, T. F. "The Administrative Component in Complex Organizations," Sociological Quarterly, Vol. 13 (1972), 533-539. 18. Kasarda, J. D. "Effects of Personnel Turnover, Employee Qualifications and Professional Staff Ratios on Administrative Intensity and Overhead," Sociological Quarterly, Vol. 14 (1973), 350-358. 19. Kasarda, J. D. "The Structural Implications of Social System Size: A Three Level Analysis," American Sociological Review, Vol. 39 (1974), 19-28. 20. Klatsky, S. "Relationship of Organization Size to Complexity and Control," Administrative Science Quarterly, Vol. 15 (1970), 428-438. 21. Lazarsfeld, P. F., and H. Menzel. "On the Relation Between Individual and Collective Properties," in A. Etzioni (Ed.), Complex Organizations: A Sociological Reader (New York: Holt, Rinehart, 1961). 22. MacMillan, A. "Ratio Variables and Inference in Studies of Administrative Intensity," (Unpublished Working Paper, Queen's University, Kingston, Ontario, 1976). 23. Meyer, M. W. "Two Authority Structures of Bureaucratic Organization," Administrative Science Quarterly, Vol. 13 (1968), 211-228. 24. Pfeffer, J., and G. R. Salancik. "Organizational Decision-Making as a Political Process: The Case of a University Budget," Administrative Science Quarterly, Vol. 19 (1974), 135-151. 25. Pondy, L. R. "Effects of Size, Complexity and Ownership on Administrative Intensity," Administrative Science Quarterly, Vol. 14 (1967), 47-60. 26. Pondy, L. R. "Toward a Theory of Internal Resource Allocation," in M. N. Zald (Ed.), Power in Organizations (Nashville: Vanderbilt University Press, 1970). 27. Pugh, D. S., D. J. Hickson, C. R. Hinings and C. Turner. "The Context of Organization Structures," Administrative Science Quarterly, Vol. 14 (1969), 91-114. 28. Rushing, W. A. "Effects of Industry Size and the Division of Labor on Administration," Administrative Science Quarterly, Vol. 12 (1967), 273-295. 29. Thompson, J. D. Organizations in Action (New York: McGraw-Hill, 1967).
