rationality and institutionalized expectations: the development … · 2010-01-09 · growth in the...

Rationality and Institutionalized Expectations: The Development of an

Organizational Set of Rules

Nikolaus Beck University of Erfurt

Nordhäuser Straße 63 99089 Erfurt

Germany

[email protected] Tel.: XX49/(0)361 737-4513

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Rationality and Institutionalized Expectations: The Development of an

Organizational Set of Rules

Abstract

The present study aims at analyzing changes of an entire set of organizational of rules over time. Moreover, it is also analyzed how the size of individual rules develops over time. The theoretical background for this study is formed by the bureaucracy theory of Weber and his successors, as well as the considerations of the New Institutionalism and contingency theory. Over time the portion of the general rule mass continues to increase. This corresponds to the considerations of the New Institutionalism, since the "general" section of the rule body examined here contains the rules that are oriented on fundamental institutionalized management principles or legal regulations. Other results suggest that institutionalist adjustment and rational management do not have to be mutually exclusive. Rather, both phenomena can exist at the same time within an organization.

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Introduction

The management literature prevailing at present does not ascribe much value to bureaucratic

rules. They are regarded as impairments of creative solutions and obstacles to organizational

learning (Hedberg et al. 1976; Nystrom and Starbuck 1984). This contempt corresponds to

the everyday life understanding of "bureaucracy": It is felt as cumbersome, as action-

restricting and hostile to progress.

However, with such a negative attitude towards organizational bureaucracy one is likely to

overlook that many approaches of organizational theory view formal rules as necessary and

valuable instruments of organizational conduct. With respect to the discussion on the benefits

of organizational rules the considerations of Max Weber concerning organizational rationality

in organizations are particularly important. He claimed that formal bureaucratic rules form

the basis of efficient modern organizations. Moreover, in his opinion formal rules play a

substantial role in the development of the Western rationalism (Weber 1976).

Another approach which pays special attention to organizational rules is the New

Institutionalism (Meyer and Rowan 1977; DiMaggio and Powell 1983). However, the agents

of the New Institutionalism do not emphasize the efficiency enhancing effect of formal rules,

as it is done in the bureaucracy theory of Max Weber. Rather, they argue that organizations

often do not implement rules for (technically) rational reasons, but because they would lose

their legitimacy, if they did not do it. Thus, organizations introduce certain rules, because it is

expected by important partners and stakeholders in their environment.

Despite the important role, which formal rules take in the organization sciences, there exist

only relatively few empirical studies, which focus on the development of organizational rules.

Most of these studies are based on the behavioural theory of the firm (e.g. March et al. 2000;

Schulz 1998a, b; Schulz and Beck 2002a; b; Zhou 1993; Kieser and Koch 2002; Beck and

Kieser 2003). These studies focus on the processes of founding, changing and suspending

organizational rules. The analysis of these processes should help to discover the mechanisms

of organizational learning since the behavioural theory – contrary to the dominant

management ideologies – regards formal rules as stores of knowledge and as crucial tools of

organizational learning.

The present study aims at another direction. Instead of analyzing specific events in the "life

course" of rules, changes of an entire set organizational of rules in time is examined.

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Moreover, it is also analyzed how the volume of individual rules develops over time. In order

to achieve theses goals longitudinal data sets of the composition of the rule body and the

volume of individual rules are analyzed. This rule body consists of the personnel regulations

of a German bank. The bureaucracy theory of Weber and his successors, neo-institutionalist

arguments, and considerations of contingency theory form the theoretical basis which is used

for the derivation of hypotheses which will be tested.

The meaning of rules in the bureaucracy theory and in Neo Institutionalism As initially mentioned Weber (1976) emphasized the special meaning of written or fixed

rules for the execution of power in organizations. For him these rules are the basis of the legal

or rational execution of power in organizations. This form of power attains its legitimacy by

the common faith in the legality of fixed regulations (Weber: 1976: 124). Thus, legal

domination in organizations is based on rationally conceptualized rules whose validity is not

questioned and which are therefore expected to be followed by the organizational members.

The power relationship between organizational members (superiors and subordinates) is

depersonalized by the validity of the bureaucratic rules. Therefore, the subordinates do not

submit to the person of the superior but only to his/her specific responsibility within a

depersonalized regime which is based on fixed rules – a thought, which emerges quite

frequently in the organizational theory following Max Weber (e.g. Clegg 1975; Gouldner

1964; Crozier 1967; Friedberg 1995). Moreover, bureaucratic administrations are

characterized by the “documentaryness” of their procedures. Systematic records are kept for

all the procedures in the organization, which are thus available for later purposes.

In comparison with other forms of governance, legal power – which in its most rational form

Weber refers to as ‘bureaucracy’ – derives its efficiency and usefulness primarily from the

mechanistic quality of a bureaucratic organization, i.e. an organization governed by rules.

Fixed rules determine work routines and, in so doing, they facilitate the precise execution of

certain tasks. Moreover, these rules may be said to constitute an order with which the

subordinates in any bureaucracy have to comply. Finally, Weber addresses the usefulness of

the division of labour – the gains that derive from specialization – within bureaucratic

organizations. The need for more efficient bureaucratic rules will therefore grow with the

realization that bureaucratic controls lead to more efficient solutions of the problems that

both organizations and states encounter (Weber 1976, 560f.). It follows that a growing need

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for ever more efficient bureaucratic structures in a business will be accompanied by an

increase in the number of bureaucratic rules. This need is thus a primary reason for the

growth in the formal rules to be found in many organizations (Burr 1998).

But Weber did not see only positive effects in formal bureaucratic rules. The basic effects of

bureaucratic power in promoting efficiency produce a remarkable double-edged quality in

bureaucratic rules. At the same time, the freedom of individuals to act and make decisions in

modern bureaucracies is limited, Weber believes, by a rampant increase in bureaucratic rules.

In this context Weber refers to what he calls the ‘iron cage’ of bureaucracy (Weber 1976).

This means that bureaucracies develop a life of their own, one from which individuals cannot

escape.

When dealing with this theory on the rampant increase in bureaucratic rules, however, other

authors have stressed the way in which members of an organization can also exploit this

situation and how, in turn, this can lead to a further increase in bureaucratic controls and – in

consequence – to even more organizational rules. In principle, organizational rules protect the

members of an organization from too strong a personal influence on the part of superiors or

customers. However, inefficiencies and rigidities may also result if an (over)strong formative

influence is exerted on an organization by bureaucratic rules and may in turn increase the risk

that personal pressures are exerted to correct these inefficiencies. This encourages the

members of the organization to devise new rules in order to restore the impersonality of

organizational power relationships and preserve their privileges (Crozier 1967; Gouldner

1964; Selznick 1949; 1943; Merton 1940).

These two phenomena – the constant need for a more efficient bureaucratic structure in an

organization and the ‘bureaucratic vicious circle’ that reduces efficiency – should also be

reflected in the set of rules investigated here. An increase in the number of rules should

reveal itself primarily in the increasing size of the set of rules, expressed in terms of the

number of pages. Clearly, the number of rules can increase without there being a growth in

the actual bureaucratic volume. Rules do not exist for ever and are often abolished if the

conditions for which they were created have changed (Schulz and Beck 2000). Moreover,

new rules inserted in the set of rules need not necessarily be as lengthy as earlier, deleted

rules. An increasing number of rules does not have to be accompanied by an increase in the

rule mass if the newly created rules contain less text than the earlier, deleted rules. Evidence

of a growing rule body will only be provided if the rule mass increases, i.e. the total number

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of pages taken up by the set of rules. Thus the following hypothesis can be put forward:

Hypothesis 1a: Over a period of time the rule mass – the size of the set of rules

expressed in terms of the total number of pages – increases.

One may, moreover, also expect an increase in bureaucratization to be reflected in the

increased size of individual rules. Those charged with devising new rules will discover

inadequacies and misleading formulations in existing rules and this will lead them to

incorporate additional points within an existing rule. Moreover, within any organization

different concerns will exist among different interest groups and these interest groups will

similarly make their needs known to those formulating the rules (Kieser and Koch 2002); in

turn, this will mean expanding the text of the existing rules. Thus, a further hypothesis can be

formulated:

Hypothesis 1b: Over a period of time the number of pages devoted to individual rules

increases.

Conversely, there is also the view that there are limits to the extent of bureaucratization

(Schulz 1998a; Meyer 1985). Sets of rules cannot be expanded at will. In Schulz’s view,

every possible issue that should be governed by organizational rules will be incorporated in

the development of a set of rules at some point (Schulz 1998a). Therefore at some point in

time there is no more room for further developments of organizational rules. Beck and Kieser

(2003) suggest, moreover, that an increase in the amount of rules can also distract the

attention of members of the organization from new problems which could otherwise be

solved by formal rules: if an ever greater proportion of day-to-day work involves the

adherence to particular rules, the potential for devising additional rules in order to solve new

problems as they appear, will be diminished. The following correlate may therefore be put

forward:

Correlate 1: The rate of growth in formal rules, as assumed in hypotheses 1a and 1b,

is not constant but declines over a period of time.

General versus specific rules

The second theoretical line of thought to be discussed here is neo-institutionalism; this

assumes that organizations must adjust to certain institutional expectations existing in each

organization’s environment so that the organizations do not lose their legitimacy and their

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chance of survival is assured (Meyer and Rowan 1977; DiMaggio and Powell 1983; Guler et

al. 2002). These expectations are created in the environment of each organization and are

brought into the organization by, for example, customers, professional associations or the

state. One may assume that organizations will embed those concepts that reflect institutional

expectations, in their general rules. This is because institutional management principles,

statutory regulations or aspects of the administration of justice are intended mostly for a

variety of organizations – they do not focus on particular organizations and certainly not on

particular activities or departments within organizations. Thus, in any set of rules these

generally applicable principles should be listed in the general section on which the

formulation of specific rules depends. Thus, in the case of the bank examined in this study,

‘Principles for human resource management’ are to be found in the chapter entitled ‘General

Matters’ in the personnel guidelines. The bank’s work rules and the most important statutory

regulations are similarly to be found in this chapter.

In the context of neo-institutionalism, reference is also made to the fact that the institutional

environment grows ever larger, gaining steadily in importance in comparison with technical

and rational considerations (Meyer 1992; Powell 1991). Organizations must therefore take an

increasingly greater note of external expectations and normative rules than of technical and

rational demands. Over a period of time this ought then to be reflected by a growth in the

proportion of the general rule mass in the set of rules.

Hypothesis 2a: Over a period of time the proportion of the mass of general rules in the

set of rules increases.

Working on the assumption that the institutional environment of an organization will expand

more strongly than the technical and rational factors on which organizational rules depend,

one may suggest that, in view of the larger number of factors that have to be taken into

account, individual general rules will increase more strongly than other rules.

Hypothesis 2b: Over a period of time the size of individual general rules becomes

larger than that of other rules.

The size and complexity of organizations

The size of an organization as one factor influencing organizational changes has been a very

frequent subject for investigation (Havemann 1993; for a review see Kimberly 1976).

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Particular prominence has been achieved by those investigations carried out in accordance

with contingency theory in which, especially, the connection between the size of an

organization and its degree of specialization has been investigated (Blau 1970, Pugh et al.

1969; Child 1972). One of the most important findings to result from this approach was the

recognition that the structural diversification of an organization increases with the growth in

the number of employees. Contingency theory also surmises that a growth in structural

diversification leads to further co-ordination challenges and thereby increases the need for

programming and planning; this, in turn, heightens the degree of formalization (Kieser 1999;

Meilich 2000). It is also the case that with increased specialization and the division of tasks

within a company the complexity of an individual task decreases and thus may be more easily

programmed by formal rules. Finally, the formal programming of an organization gives the

company management the opportunity of retaining control over supervisors at subordinate

levels, despite the increased complexity of the organization and the delegation of decision-

making implied by this increased complexity.

These findings, derived from contingency theory, are long established but they are

nevertheless questionable. There are two reasons for this. First of all, in studies within

contingency theory different indicators were used to measure structural elements that are

often difficult to compare with one another. The degree of formalization was constructed

almost exclusively by means of questions about the existence of formal rules for different

organizational aspects. But these questions were formulated in a different way for almost all

the studies and were also often aimed at different sub-categories of formalization (see

Kubicek and Welter 1985: 700 ff.). Moreover, the majority of the formalization measures

depended on the individual assessment of those questioned in the organization. Only very

rarely were the actual dimensions of organizational documents and rules taken into account

when measuring the degree of formalization (e.g. Blau and Schoenherr 1971).

Moreover, in empiric studies within the approach of contingency theory the relationship

between the degree of structural differentiation, i.e. the formalization of an organization, and

the size of the organization was investigated only in a cross-section. Thus, these studies failed

to test the implicit assumption that growing organizations would heighten their degree of

formalization. The results deriving from the application of contingency theory do not,

therefore, necessarily substantiate the view that there will also be greater formalization within

any one organization if it increases its number of employees or the number of its structural

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units.

The analysis of the set of rules of a single organization over a period of time, presented in this

paper, offers a more precise view of the connection between, on the one hand, the growth of

an organization and, on the other, the degree of formalization governed by the amount of

written rules. The size of the organization is measured here not only in terms of the number

of employees but also in terms of the number of branches. The number of branches is an

indicator of structural diversification, more precisely of the regional diversification of a bank.

Since an increasing number of regional units is accompanied by an increase in the co-

ordination efforts of the organization as a whole, which in turn have to be managed by means

of formal rules, a growth in the number of branches also ought to lead to an increase in the

degree of formalization in the organization. Moreover, the greater degree of formalization

caused by company growth should not only be accompanied by a further increase in the rule

mass but also be reflected in a lengthier text for the individual rules. Thus, the following

hypotheses are put forward:

Hypothesis 3a: An increase in the number of employees and an increase in the

number of branches are accompanied by an increase in the rule mass.

Hypothesis 3b: An increase in the number of employees and an increase in the

number of branches are accompanied by an increase in the number of pages devoted

to individual rules.

Several studies within the approach of contingency theory suggested that the growth in

specialised units and/or tasks declines as the number of employees grows because there is a

decreasing marginal utility of specialization when the complexity of an organization is

growing (e.g., Blau and Schoenherr 1971; Child 1972; Kieser 1973; Pugh et al. 1969). Thus

the formalization that results from the degree of specialization should increase with shrinking

increments in relation to the number of employees and branches. Therefore, the following

correlate can be formulated:

Correlate 2: The growth in formal rules, as assumed in hypotheses 3a and 3b, is not

constant but declines with the increased number of employees and branches.

Specialization of the rules

The degree of specialization in an organization ought to be reflected above all in the ratio of

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specific rules to the general rules applicable to the organization as a whole. This is because

specialised activities in organizations require specific guidelines to regulate these activities

whereas general rules deal primarily with basic activities, which remain relatively

independent of the degree of specialization of an organization. Thus, one may conclude that

an increase in the number of employees will above all lead to a growth of specific rules and,

consequently, that the proportion of specific rules in the set of rules will grow as the number

of employees increases. Once again, it may be assumed that the number of branches also

correlates with the proportion of specific guidelines since it is necessary to create specific

rules in order to deal with specific regional issues. This can be formulated, as follows:

Hypothesis 4a: With a growth in the number of employees and in the number of

branches the number of pages devoted to specific rules (the specific mass) in the set

of rules increases.

Hypothesis 4b: With a growth in the number of employees and in the number of

branches the number of pages devoted to individual specific rules increases more than

the number of pages devoted to general rules.

Because of the declining marginal utility of the specialization, an increase with shrinking

increments in the proportion of specific guidelines ought to become apparent if there is a

growth in the number of employees and branches. However, it may be assumed there will be

decreasing positive effects on the proportion of the mass of specific rules anyway since the

proportion of specific rules is limited. Therefore a degressive positive effect would have a

purely ‘technical’ character. For this reason no additional correlate appears here.

Data and methods

As already explained, this study investigates the development of personnel guidelines in a

bank. This bank is a medium-sized, private financial institution founded in the nineteenth

century; its branches and agencies are located primarily in South Germany. The set of rules

containing the personnel guidelines which are examined here, was introduced in December

1970, i.e. long after the foundation of the bank. Thus, a set of rules was created for an

organization that already had considerable experience. This study concentrates on personnel

guidelines for one very simple reason: the author’s contacts in the bank requested that this

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section of the set of rules should be selected for investigation because it deals with a less

sensitive area in the bank’s activities than, for example, regulations governing loans.

Whenever new rules were introduced or existing rules modified, the pages containing the new

text of the rules was distributed among the members of the organization. At the same time,

the covering sheet for the ‘exchange batches’, as they were called, stipulated which pages

were (if applicable) to be removed from the set of rules, and which and how many pages were

to be inserted in the set of rules. Thus, by referring to these covering sheets it was possible to

follow the development of the exact number of pages devoted to an individual rule – this was

necessary to determine both the size of individual rules and the rule mass over a period of

time.

An indexed table of contents with the headings of individual chapters provided information

about both those individual chapters and sub-chapters. Figure 1 shows a stylized example of a

rule. A note at the top of the page indicates that it concerns a personnel rule; below this, the

index code for the rule appears and, next to this, the precise titles of the chapter and sub-

chapter are given, identified by index numbers. This example concerns a rule taken from the

chapter on ‘Employee Support’, sub-chapter ‘Employment Contract’. The rule itself concerns

the notification and transmission of personnel data. The vertical line next to point 1.2

indicates that, in comparison with the previous version of this rule, an amendment has been

introduced.

Dividing the rules into general rules and specific rules was effected without difficulty: the

personnel guidelines contained a chapter entitled ‘General Matters’, as has already been

mentioned; this chapter contained every personnel rule which dealt with matters that came

from outside the bank. All the other chapters contained specific rules.

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Insert Figure 1 about here

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The set of rules was comprehensively revised in 1989. It was primarily slimmed down in that

some rules were deleted and others amalgamated. As this offered a clear caesura in the life of

the set of rules and as only one month for the year 1970 was available for inspection, the

analyses presented here deal with the period between the beginning of 1971 and the end of

1988.

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Dependent variables

In testing the hypotheses three different dependent variables had to be analysed:

• first, the development of the whole (global) rule mass was investigated, i.e. the

change in the number of pages devoted to all personnel guidelines over a period of

time;

• then the variation in the ratio of general rules to specific rules was analysed over a

period of time;

• finally, the change in the number of pages devoted to each individual rule was

examined.

In investigating these three different processes two different sets of data were required. In the

case of the first two processes, which relate to hypotheses 1a, 2a, 3a and 4a, a time-series data

set was established; this data set contained data concerning the rule mass, recorded at semi-

annual intervals, the proportion of the specific rule mass and other time-varying variables.

This set of data contained 36 observations.

The rule mass, i.e. the whole amount of personnel rules expressed in terms of the number of

pages devoted to them, could be determined by adding together the number of pages devoted

to each individual rule in existence in a given semi-annual period. Since, changes occurred in

the number of pages devoted to the rules during intervals, average values had to be

established. For this reason, the average number of pages devoted to each rule was calculated

for each interval and multiplied by the number of rules that were ‘alive’ in the particular

interval. In investigating the proportion of the mass of specific rules this procedure was

repeated for each rule not listed in the chapter ‘General Matters’. The proportion of this mass

to the whole rule mass constituted the proportion of the specific mass.

In order to investigate the number of pages devoted to individual rules, i.e. in testing

hypotheses 1b, 2b, 3b and 4b, a completely different data set was necessary, namely a data set

that tracks individual rules longitudinally. To accomplish this, the complete ‘rule history’ of

each individual rule was determined and all changes in the page numbers for these rules were

recorded. The history of the individual rules was then split into monthly sub-episodes so that

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the changes in the amount of pages devoted to individual rules could be recorded month by

month. This splitting into months produced a data set amounting to 23,877 observations.

Methods

For the investigation of the rule mass (hypotheses 1a and 3a) and for the analysis of the ratio

of the mass of specific rules (or general rules, respectively) to the total rule mass (hypotheses

2a and 4a), linear regression models were calculated. Since, as is often the case with

regressions for time series, there was an autocorrelation of the residuals, GLS-estimators for

an “First-order autoregressive”-process – AR(1)-process – was applied (e.g. Griffiths et al.

1993, chapter 16). For the model εβ ttt +x =y ′ the following assumption on the error term is

made:

with ( ) , N u 2ut σ0= . For the calculation of the autocorrelation parameter ρ (rho) a Prais-

Winsten-estimator was applied (Greene 1998: 308). Since in AR(1)-models the coefficient of

determination (R2) cannot be interpreted in the usual way, it will not be presented here.

However, in these models a likelihood function is calculated. Therefore it is possible to

calculate a chi2 value with the log-likelihood of the restricted model stemming from an OLS-

model with only a constant.

As already indicated, the dependent variable used in investigating the size of individual rules

consisted of the number of pages devoted to each individual rule, updated monthly during the

investigation period. In this context it should be noted that the number of pages could change

only at the inception of a new version of a rule and that, logically, it had to remain constant

for the duration of the existence of a rule version. Two further particular features should be

noted with respect to investigating rule size:

1. The data set used in examining rule size has the character of a panel: over the course

of the investigation period several observations exist for each individual rule. In order

to deal correctly with the panel character of the data specific procedures are required;

primarily to limit or, if possible, to eliminate the problem of unobserved heterogeneity

that frequently occurs in panel data (Griffiths et al. 1993: 571 ff.). Take, for example,

,u += t1-tt ερε

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the case of rules introduced later in time that are lengthier than the older rules: unless

this heterogeneity is controlled for, time will have a positive effect on the rule size

even though this effect need not have anything to do with the change in the size of

individual rules.

2. There exits censoring of dependent variables. The lowest registered size of rule

amounted to one page. Because of such censoring, spurious estimations of the effects

of independent variables can be made and the more the observations lie precisely on

the censoring threshold, the greater these spurious estimations become. In the data set

used here almost half the observations belong to rules whose size amounts to one

page.

In order to account for these particular features in an appropriate manner a random effect

Tobit-model was applied. Tobit models account for the threshold value of the dependent

variable in such a way that it is possible to formulate a normal regression model for a latent

variable Y*. Random effects are error components, iµ , which capture the deviations of the

units of analysis (here: the rules) from the population constant α in a random way and are

constant over time. They are calculated in addition to the error terms for the individual

observations (εit). In this study the individual observations are the monthly sub-episodes of

the rules. The random effect Tobit model can be formulated as follows:

ititiit xy εβα +′+=* , with ii µαα +=

However, the observation of the dependent variable is only possible for values on and above

the threshold. With respect to the observed variable Y it is assumed here that

1=ity , if 1* ≤ity

*itit yy = , if 1* >ity

The Tobit model is formulated as a maximum-likelihood model in which the probability of

the observed values and the probability of censoring contribute to the likelihood. In this study

also the portion of the variance which derives from the constant error components (Rho) is

presented.

Independent variables

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It remains to describe briefly the independent variables used in the statistical models.

- Time: the time used was calendar time. In the models in which the panel data set was

used time was measured in weeks at the beginning of a sub-episode. In the models in which

the basis of the data was a time series, calendar time was measured every six months. In both

cases the values for this variable were converted into annual values. In the panel data set the

first sub-episode was given the value 0 and in the time-series data set it was given the value

0.5.

- Number of employees: the number of employees could be determined from the

company reports and could be brought up-to-date annually. In the regression models the

minimum number of employees was subtracted from this variable in order to avoid

unrealistic constants. This variable was also divided by 1000 in order to produce ‘visible’

effects.

- Number of branches: the number of branches could similarly be determined from

company reports and could be brought up to date annually. Once again, the smallest value

was deducted in each case. This variable was divided by 10.

- In order to test the possible non-linear influence of the variables described above, as

assumed in the correlates, also logged values of time, the number of employees and the

number of branches were used in the regression models. In so doing, the natural logarithm

was calculated for the initial values actually observed and then, once again, the smallest value

was subtracted.

- Specific rules: in the Tobit models all rules not falling within the area ‘General

Matters’ were defined as specific rules and received the value 1 while general rules were

allocated the value 0. This variable was also multiplied by the time, the number of employees

and the number of branches, in order to calculate the effects of the interactions treated in

hypotheses 2b and 4b. Moreover, interactions were also built with general rules coded with 1

and specific rules coded with 0. This was done in order to estimate models with conditional

main effects instead of interaction effects.

Control variables

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- Size of board: in a couple of studies on organizational change (e.g. Goodstein et al.

1994) it is often argued that a large board of executive directors must have a negative

influence on change in an organization since there is less cohesion within large

heterogeneous groups and, furthermore, they offer only limited possibilities for effective

communication (Judge and Zeithaml 1992) and only limited possibilities for participation

(Shaw 1976). Conversely, others also argue that the introduction of new board members (and

thus an expansion of the board) increases contacts to the business environment and to

relevant information in this environment and that this, in turn, ought to produce additional

stimulus for organizational changes (Nyström and Starbuck 1984; Virany et al. 1992). This

study examines what influence the size of the board has on the development of the set of

rules in view of the fact that most organizational changes are based on rule changes.

The number of board members could also be determined from company reports. As all

changes in the board were recorded in company reports, together with the exact date of the

change, an up-to-date monthly tally of the size of the board could be established. For those

models in which time series were used, the size of the board could be constructed in terms of

the average number of board members available for each six-month interval.

- Strike: finally, it is necessary to test the extent to which critical situations in the bank’s

business environment had an influence on the development of the set of rules. Undoubtedly,

strikes in the banking industry rank among the critical situations that arise in the bank’s

business environment. There were strikes in the banking industry in 1974, 1986 and 1987.

Thus, when establishing a dummy variable ‘strike’, all sub-episodes or six-month periods

falling within 1974, 1986 or 1987 were coded 1; all other years were coded 0.

Results:

The descriptive statistics and the correlations of the variables for both data sets can be seen in

tables 1a and 1b. The descriptive statistics of the number of employees and the number of

branches, together with the interaction variables are shown for the initial variables and not as

deviations from the smallest value, as used for the correlations and the multivariate models.

During the investigation period the bank had between 10,388 and 12,136 employees and

between 417 and 478 branches. The size of the board varied considerably: the number of

board members amounted to between 6 and 14 during the investigation period.

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Insert tables 1a and 1b about here

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Models for the development of the global rule mass and the specific rule mass

The results of the AR(1) model in explaining the rule mass and the proportion of the specific

mass can be seen in table 2. In the case of the first model the effects of the non-logged

variables on the rule mass are shown and in the second model the effects of the logged

variables. It should be noted that the control variables were always used in their non-logged

form. Then the effects of the non-logged and logged variables on the proportion of the

specific mass are shown. In this case also, the control variables were always used in their

non-logged value.

A clear increase in the rule mass can be seen over a period of time, as assumed in hypothesis

1a. No conclusion can, however, be made about whether this increase is linear or with

shrinking increments: the non-logged and the logged formulations of the course of time lead

to highly significant effects in each case. Hypothesis 3a is only partially confirmed: the

number of employees has no effect on the rule mass, neither in the logged nor in the non-

logged form. However, with the number of branches the rule mass increases in a highly

significantly way. But no non-linear increase can be found. Only the non-logged form of the

number of branches produces this result.

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Insert table 2 about here

----------------------------------------------

A strike in the organization’s environment does not influence the rule mass whereas the size

of the board tends to lead to a decrease in the number of pages in the set of rules.

The likelihood-ratio chi2 test produces a slightly higher value for the model with logged

variables; nevertheless, one cannot assume that correlate 1 is affirmed on account of the basis

of the strength and significance of the individual effects, especially as far as the number of

branches is concerned.

Over the course of time the size of the mass of specific rules declines significantly. Thus, the

amount of general rules in the set of rules grows – which is in accordance with hypothesis 2a.

18

The logged number of employees proves to have only slight influence whereas the size of the

mass of specific rules shows significant growth with the logged value for the number of

branches, thereby lending partial support to hypothesis 4a. In view of the high median

proportion of the mass of specific rules and in view of the limitation of the dependent

variables (more than 100% in the specific mass is not possible) it is not surprising that the

linear term of the number of branches should produce no significant effect. The control

variables have no influence on the size of the specific mass. This is also the case if the size of

the board is logged (not presented here).

Models for the development of individual rule size

Finally, the effects of the independent variables on the number of pages devoted to individual

rules can be seen in table 3. The following procedure was chosen: as hypotheses 2b and 4b

assumed differences in the effect of independent variables for general and specific rules, the

effects of time, of the number of employees and of the number of branches were first

calculated as conditional main effects for general and specific rules. In addition, by creating a

parallel model of ‘classic’ interaction effects the differences between these effects was tested

for their significance. For the sake of greater clarity, since all other effects retain their

respective values here, they are not presented again. In the case of the LR test statistics, no

differences to the model with conditional main effects exist here either. Once again, the

models were calculated first with non-logged values for the period of time, the number of

employees and the number of branches and, subsequently, with the logged values.

---------------------------------------------

Insert table 3 about here

---------------------------------------------

It becomes clear that specific rules are lengthier than general rules – the effect of the

respective dummy is positive and highly significant. Table 3 also shows clearly that – as

assumed in hypothesis 1b – the size of each individual rule grows to a highly significant

degree over time; this is the case of both the non-logged and the logged formulation of time.

On the other hand, hypothesis 2b is not confirmed. On the contrary, specific rules increase in

size more strongly than general rules. The difference in the effects is significant only in the

case of the non-logged formulation of time. Hypothesis 2b is not, however, supported in any

model – a result that will be discussed in more detail in the following section. Hypothesis 3b

19

is partially confirmed: an increase in the number of employees leads to an increase in the size

of individual rules. But, there is no significantly stronger increase here in the size of specific

rules as assumed in hypothesis 4b. The increase in the number of employees has a tentatively

stronger effect on the individual number of pages devoted to specific rules than on the size of

general rules. Again, in view of the strength and significance of individual effects in the

different models one cannot say whether the number of employees has a linear effect on the

rule size or one with shrinking increments.

The influence of the number of branches on the rule size shows a somewhat different picture:

as assumed in hypothesis 3b, this is positive only for non-logged formulations of the number

of branches. In the case of general rules – which, admittedly, make up only a relatively small

part of the set of rules – an increased number of branches is even accompanied by a reduction

in the rule size. It is also evident that the effect of the number of branches is significantly

greater for specific rules than for general rules. This supports hypothesis 4b as far as the

number of branches is concerned, at least in the model with non-logged variables where the

number of branches has a significantly positive effect on specific rules.

Both a strike and a growth in the size of the board resulted in a shrinking of the rules. Using

the chi2 values for both models it may be assumed that the model without logged values for

time and the numbers of employees and branches is the more appropriate: here the chi2 value

is clearly higher. Thus, correlate 1 and 2 receive no support.

Discussion:

The aim of this study was to examine the development of a set of rules against the

background of neo-institutional considerations and considerations of contingency theory. A

longitudinal data set of the personnel guidelines of a bank was examined and, with this data

set, the size and specificity of the entire set of personnel rules and the development of the size

of individual rules could be analysed over a period of time. In testing hypotheses about

contingency theory, this form of analysis represents a marked advance on previous empirical

studies of formalization within this approach in that in those studies only cross-sectional data

were used and the degree of formalization was constructed by strongly subjective indicators.

To a large extent, the hypotheses put forward on the basis of these theoretical approaches

could be supported empirically. The observations made by Max Weber and his followers,

20

which assume an increase in bureaucratic rules over a period of time, could be wholly

confirmed. According to Weber, the reasons for this can be found in the constant need to

increase efficiency by finding solutions to organizational problems, solutions that can be

provided by fixed rules designed in accordance with rational criteria. On the other hand, those

of Weber’s successors who examined bureaucracies stress the need to protect members of an

organization from personal influences, something that can be achieved by establishing formal

rules. In this study both the total number of pages of personnel guidelines and the number of

pages of individual rules increased over time.

The assumptions contained in the contingency theory could also be supported in the findings

of this study. As the complexity of the organization increased – measured in terms of the

number of employees and branches – the set of rules became more voluminous. The

increased requirement and/or advantageousness in formalizing and specializing courses of

action in the organization leads to an increase in formal rules. Interestingly, only an increase

in the number of branches – not a growth in the number of employees – leads to an increase

in the rule mass. A significant increase in the number of pages devoted to individual rules

can, however, be observed with an increasing number of employees. This means that with a

growth in the number of employees individual rules increase in size, while at the same time a

growth in the number of employees must lead to an increase in the death rate of rules. This is

precisely the result recorded in the studies undertaken by Beck (2001) and by Schulz and

Beck (2002a) which used the same data as the present study in order to estimate death rates

of rules. Therefore the growth in employee numbers does not lead to an increase in the rule

mass. An increase in the number of employees not only makes the expansion of existing rules

necessary, it also requires the suspension of rules as these often cannot be reconciled with the

increasingly more complex standards and demands made by employees. In addition, with an

increase in the number of branches, the number of pages devoted to individual specific

guidelines grows markedly more strongly than those devoted to general rules which even

decline in size with an increase in the number of branches. This underlines the great

importance of specific rules in the co-ordination of an organization that has grown in

complexity.

The most interesting results, however, were provided by the examination of neo-institutional

hypotheses: over the course of time the proportion of the general rule mass becomes

increasingly larger. This corresponds to neo-institutionalist considerations since the section

21

entitled ‘General Matters’ in the set of rules functions as a kind of collecting point for rules

which address fundamental institutional management principles or statutory regulations.

External, institutional expectations are normally reflected in the general section of the set of

rules examined here. Thus, the increase in the proportion of the general rule mass

corresponds to the importance of institutional norms and expectations growing over a period

of time. However, at the same time, the number of pages of individual general rules does not

increase more strongly than specific rules but markedly less strongly. This means that the

growth in the proportion of the general rule mass can be explained by a larger number of

foundings of general rules, a result which has previously been found by Beck (2001).1

It is, naturally, impossible to provide a conclusive explanation for the discovery that, over

time, general rules are included in the set of rules in larger numbers but thereafter increase in

size at a slower rate than specific rules. But this finding may relatively well support several

other recent findings of neo-institutional research. Organizations are confronted with the

problem of satisfying institutional expectations and, at the same time, meeting the specific

demands arising within their confines. This is why organizations develop strategies that

enable them to act independently without disappointing the institutional environment (e.g.

Walgenbach 2000; Walgenbach and Beck 2003; Boiral 2003). Although in this particular

case the organization adjusts its set of rules to institutional norms, any further engagement

with these rules – with the aim of amending and thereby refining their content – happens less

often than with rules that control the specific courses of action by the organization. For the

organization under examination it is clearly more important to control concrete internal

working practices as rationally as possible than it is to attempt to make the organization’s

rules conform more closely to institutional expectations.

On occasion, organizations even avoid conformity to institutional norms if their internal

structures do not accord with institutional management concepts (Beck and Walgenbach

2003; in press). To this extent, the neo-institutional belief that ‘(e)very aspect of rationalized

organizational structure comes under exogenous institutional control’ (Meyer 1992) does not

apply. It is impossible to resolve here whether, in the case of the organization under

examination, this also means a decoupling of structures and activities (Meyer and Rowan

1977; Westphal and Zajac 1998; 2001). A decoupling of this kind would exist if those general

rules that had been incorporated in the set of rules following institutional pressure were no 1 An alternative explanation would be a lower death rate for general rules. Such a finding was, however, not noted by either Beck (2001) or Schulz and Beck (2002a).

22

longer considered as important once they had been formulated and if the members of the

organization failed to abide by these rules. It was not possible, however, to examine this issue

in this study. Nevertheless, the conclusion that organizations are able to conform to

institutional expectations without thereby renouncing independent, rational control of their

specific activities, can to a certain extent reconcile the sociological approach of neo-

institutionalism and the classical business perceptions of a rational manager. Conformity to

institutional norms and rational management do not appear to be mutually exclusive, as is

sometimes still suggested. In fact, it appears that both phenomena can exist within one

organization.

No support could be found for the two correlates that assume an increase in the rule mass

with shrinking increments and/or rule size with independent variables. One reason for this

could be that the variance of the independent variables in the investigation period was

insufficiently large to allow such an influence with shrinking increments to develop.

Conclusion

Hitherto, organizational rules have only rarely been used as the subject of empirical analyses

even though in recent years the interest in the study of the development of organizational

rules and routines has grown. In the present study the data concerned with an individual set of

rules applicable to one organization was analysed. It is, therefore, desirable that this kind of

analysis should be employed in the examination of other sets of rules in other organizations.

As the results of this study show, analyses of this kind can offer valuable insights in the

testing and developing of organizational approaches.

23

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Table 2: Regression models of the development of rule masses (N=36)

Rule mass (H1a, H3a)

Proportion of specific mass

(H2a, H4a) non-logged

values logged values

non-loggedvalues

logged values

Constant 86.620***(23.662)

159.911***(36.431)

82.373***(23.285)

82.226*** (2.826)

Time

18.400***(1.196)

78.069*** (11.789)

-0.441* (0.188)

-3.192** (0.949)

N of employees

-9.062 (9.320)

5.102 (107.846)

1.722 (1.266)

20.704+ (12.614)

N of branches

10.033***(2.604)

-0.755 (157.238)

0.357 (0.369)

38.443* (17.621)

Strike 6.358 (7.288)

7.185 (6.251)

-0.160 (0.905)

-0.238 (0.849)

Size of board -1.826 (1.675)

-2.895+ (1.522)

0.015 (0.214)

0.003 (0.196)

Rho 0.630*** 0.950*** 0.733*** 0.719*** N 36 36 36 36 χ2 (DF) 152.7 (6) 155.8 (6) 52.6 (6) 57.6 (6)

* p<0.05 **p<0.01 ***p<0.001 +p<0.1 standard deviations in parentheses

29

Table 3: Regression models of the development of individual rule size (N=23,877)

non-logged values

logged values

condition. effects

difference condition. effects

difference

Constant 1.159*** (0.097)

0.594*** (0.150)

Time General rules

0.030*** (0,004))

0.193*** (0.028)

Time Specific rules

0.042*** (0,002)

0.012** (0.004)

0.241*** (0.013)

0.047 (0.030)

N of employees General rules

0.117*** (0.034)

1.559*** (0.374)

N of employees Specific rules

0.165*** (0.019)

0.048 (0.038)

2.244*** (0.205)

0.686 (0.414)

N of branches General rules

-0.034* (0.014)

-2.764*** (0.633)

N of branches Specific rules

0.034*** (0.007)

0.068*** (0.015)

-0.457 (0.340)

2.307*** (0.662)

Specific rules 0.880*** (0.101)

0.787*** (0.159)

Strike -0.054** (0.020)

-0.054** (0.021)

Size of board -0.019*** (0.004)

-0.024*** (0.004)

N 23877 23877 Rho χ2 (DF)

0.833 7246.8 (9)

0.833 7103.3 (9)

* p<0.05 **p<0.01 ***p<0.001 standard deviations in parentheses

30

Figure 1: Stylized Example of a Personnel Rule

- 1 - The Rule Body Personnel 8-2-5 Employee Support - Employment Contract – Transmission of personnel data __________________________________________________________________ 1 Announcement of addresses and changes of employees’ names 1.1 Information of superior

The addresses and names of employees have to be constantly updated. Please inform your superior immediately if your address or name (e.g. because of marriage) has changed..

1.2 Information of the divisions of employee support The subsidiaries report constantly to the divisions of employee support - Changes of employees’ names - Changes of employees’ addresses - Corrections on employees’ personal records.

2 Transmission personal records Personal records have to be sent constantly to the respective regional division of employee support. Date: 81-04-23

rationality and institutionalized expectations: the development … · 2010-01-09 · growth in the...

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