Attributions, cognitive processes and control systems

Accounting, Organizations and Society. Vol. 6, No. 1, pp. 69-93. © Pergamon Press, 1981. Printed in Great Britain.

0361-3682/81/0301-0069502.00/0

A T T R I B U T I O N S , C O G N I T I V E P R O C E S S E S A N D C O N T R O L SYSTEMS

MICHAEL D. SHIELDS School of Business Administration, The University of North Carolina at Chapel Hill

JACOB G. BIRNBERG* and IRENE HANSON FRIEZEt Graduate School of Business,* Department of Psychology, t

University of Pittsburgh

Abslxact

This paper reports two experiments which are designed to provide insights into how superiors and subordinates make perceptual or cognitive mappings from accounting signals to causal agents. The experiments focus on superiors' and subordinates' information seeking and causal attribution utilization to explain the subordinate's reported performance. Particular attention is given to (1) asymmetric causal attribution utilization by the superior and the subordinate and (2) the attribution mappings the two actors make when they receive ambiguous signals about the subordinate's reported performance.

The existence of a superior-subordinate relationship may require that some form of periodic review of the subordinate occurs. The review is to the potential advantage of both actors because the rewards obtained by the subordinate often are a function of his or her performance. Similarly, the rewards accruing to the superior may be, at least in part, a function of the subordinate's performance.

A complete review of the subordinate's performance may require that at least two questions be answered: firstly, did the subordinate attain the standard of performance expected? Secondly, regardless of the answer to the first question, it may be desirable to ascertain why the performance was above or below the standard. Thus, the review process usually consists of no less than three steps: (1) the setting of a performance standard; (2) the measurement and classification of perfor-

mance relative to the standard; and (3) ascertaining the cause(s) of the reported

behavior. Some researchers have viewed the review

process in an essentially mechanical fashion (Demski, 1976; Demski & Feltham, 1978; Baiman & Demski, in press). Thus, these researchers essentially ignore all three steps in the review process. Others, however, have recognized the

significance of the steps in the review process. Their focus has been on the behavioral issues involved in standard setting and the role of performance indicators as affectors of behavior (Caplan, 1971; Hopwood, 1974; Lawler & Rhode, 1976). For the most part, however, the latter studies assume that the answer to the third step - causality - is known, can be learnt without cost, or irrelevant.

Recently, a new thrust of behavioral research has emerged which is concerned with the third step. These papers have evolved in both the behavioral accounting literature and the organizational behavior literature. Typical of the former are the works of Birnberg etal. (1977)and Shields (1980a). In the latter area, much of the research has centered around the work of Mitchell (Green & Mitchell, 1979; Mitchell & Wood, 1980; Green & Liden, in press). In each literature, while there has been a focus on different questions, the significant point is that both recognize that causality is usually not known in an objective fashion. The result is that the superior and subordinate can hold different views of causality for the subordinate's reported performance and that the superior may be incapable of ascertaining with any degree of objectivity the cause(s) of the reported behavior. Thus there are significant

69

70 MICHAEL D. SHIELDS, JACOB G. BIRNBERG and IRENE HANSON FRIEZE

opportunit ies for conflict in the multi-person control system.

This paper focuses on the superior's and the subordinate 's use o f accounting data to make inferences concerning causality. As indicated earlier, both actors draw these inferences for at least two int imately related reasons. One is to establish the underlying cause(s) of the behavior. This is called attribution. The other reason is the allocation o f the extent o f responsibility to the subordinate for the reported performance. This is called evaluation.

In a world of certainty, the at tr ibution task is trivial. Even in a world where hindsight is costless (or, the oppor tuni ty cost is less than the expected benefit from possessing it), the at tr ibution is trivial. However, in the world as it in fact exists, the at t r ibut ion is not trivial. 1

To model how actors in control systems make attributions based on feedback information, Birnberg et al. (1977) proposed an at tr ibution theory based model of the management control system. The two experiments reported in this paper focus on one of the cases where the actor(s) has less than 20 -20 hindsight - the temporal and physical separation o f the superior from the subordinate while the latter is performing the task. 2 This paper provides evidence pertaining to: (1) the superiors and subordinates use of feedback

data to make initial attr ibutions, which are made before a variance investigation is undertaken, for the subordinate 's reported performance;

(2) whether or not these two actors tend to use the same or different initial at tr ibutions to explain the subordinate 's reported performance in two information states (ambiguous and unambiguous); and

(3) the information seeking patterns - variance investigations - o f a superior and a subordinate as they a t tempt to verify their initial a t t r ibut ion as to the cause o f the

reported performance. In the following sections, the Birnberg et al.

model is discussed and the relevant literature in psychology and organizational behavior reviewed. Next, the two experiments are reported and the implication of their results for future research is discussed.

LITERATURE REVIEW

The management control process contains cognitive processes and multiple actors. Figure 1 is a model o f the control process with two actors, the superior and the subordinate. There are several cognitive processes which are present for both actors (Fig. 2). These include processing (reviewing) the feedback report, making an at tr ibution, a variance investigation decision and an expectancy. Cognitive processing is also aimed at assigning responsibility for the subordinate 's reported performance which is not necessarily a straight- forward process. As is discussed later, superior and subordinate may disagree as to the assignment of responsibili ty especially in an ambiguous information state. The reader should note that the flow of Fig. 2 begins in the lower righthand comer.

The emphasis of the at tr ibution control process model in Figs. 1 and 2 is how people process information about achievement behavior. Two key aspects of the model are the utilization of already acquired information - from memory and feedback reports - to initially at tr ibute reported performance 3 and information seeking after making an initial causal at t r ibut ion (a variance investigation). It is these two aspects o f the model which are examined in this paper.

The subordinate's activity The original Birnberg et al. (1977) model

followed the tradit ional practice of viewing the subordinate 's activity as a black box either

i There are at least three real world situations where the act of attribution is nontrivial: (1) a temporal and/or physical separation between the superior and the subordinate/task; (2) a complex or uncertain situation in which the mapping from input to output for the subordinate's activity is not obvious; and (3)when the superior is unable to obtain (reliable) measurements about the subordinate's performance.

2 See Note one. Three examples of the physical/temporal separation are: (1)a cost analyst who scans a vast array of feedback information about several tasks and has little or no physical contact with the tasks; (2)a centralized organization where higher management makes planning and control decisions for operating units at other locations; and (3) a sales manager controlling the performance of a salesperson.

3 One assumption made in the Birnberg et al. (1977) model is that people do make attributions when not requested to do so. Substantial research in control-like settings supports this assumption (e.g. Carroll & Payne, 1977; Smith & Hunt, 1978).

ATTRIBUTIONS, COGNITIVE PROCESSES AND CONTROL SYSTEMS

I Cognitive I processes

Budget

Superior I Subord ina fe !

, Budget

1

' Feedback

I re°a" I

processes I J

I I activity

1 Feedback report

Cognitive l, I

Fig. 1. A model o f the management control process with cognitive processes and multiple actors.

71

.~ Revise causal I ' - - - - / ~ ~ / attribution / I

/ t / /

Form I Initial I - causal expectation ,j_ ~ L, attribution

Start

Fig. 2. Cognitive processes o f an actor in the management control system. Key: cognitive processes are in rectangles; management activities are in elipses; information cues are in diamonds; - - - possible route ff investigation is deemed necessary.

I (Non) J accounting data I

MICHAEL D. SHIELDS, JACOB G. BIRNBERG and IRENE HANSON FRIEZE

impenetrable from our limited external perspective or as one whose structure or contents are an irrelevancy. This is incongruous for the very focus of the control process is ascertaining the details of what occurred during the activity phase. It is notable that, in practice, reporting about the activity (the scorekeeping function) is an important element of the accounting function. Insights about the elements perceived to compose the subordinate's activity are needed to aid actors in evaluating the past behavior and in planning future activities. Thus, as much of the relevant details about the activities as possible ought to be provided.

To deal with this issue, the subordinate's activity box has been subdivided initially into two parts - "task environment" and the "subordinate" (e.g. foreman) responsible for performing the task (Fig. 3). Then, because the task environment is so global a term, that portion is subdivided into the task itself and the "workers" present in the task environment. In this way, the model in Fig. 3 is

Formal investigation

External ] moti va tars

Superior's activities

Su bordinate's activities

External ~ motivators

(Non) Accounting

data

Suberdinafe Task environment

Task I Workers

Fig. 3. The subordinate's activity.

more realisti~ for it structures the activity box in the same manner as actors engaged in the activity may view it.

Figure 4 brings together the various parts of the Birnberg et al. model that were presented in Figs. 1, 2 and 3. Figure 4 is drawn in the context of an imposed standard setting process. Of course, it could be changed to incorporate a participative standard setting process.

At t r ibu t ion theory - a br ie f view Attribution theory is an attempt to describe

how people cope with information incompleteness (Jones et al., 1971; Shaver, 1975). (For a current

I i i t I Form intervention

expectation ( If needed) '

F ----] I I I

Initial I causal attribution

Other data I j Re~ (includes memory),,j =j prior c

[ Subordinate's activity~ | ....... I Task --7 | [ environment

" - - - . I Subord- I I I" ! 1 inote ITo. t Wor~e,s I I

Setpersona, I [ Form ] [ Init,al l _ l budget I"1 expectation /-; I causal r'--I l ) i " I I attribution I l

/ I I , - - - l - - - - - L , I I / I I I r " ......... i I I l l Informal investigation

I ooo a, 1 " I ,nterveot,o,, 1--] o."',o,,oo F II

+___ Rev'c~Iv,t~ i

t . "l Feedback J

re,o?,, ,1

"I e°d°ac"t report I

Review prior activity

I

Other data (includes memory)

72

Fig. 4. A revised control system model. Key: usual path; - - - possible path if investigation is deemed necessary.

ATTRIBUTIONS, COGNITIVE PROCESSES AND CONTROL SYSTEMS 73

view of the achievement motivation attribution literature, see Weiner, 1974.) Simply stated, it is concerned with people's information seeking behavior and their use of this information in assessing the cause(s) of observed or reported outcomes or behaviors. The scope of the theory also includes people's perception/decision as to locus of control. Its primary focus is on those situations where the cause is not obvious or the signals are conflicting. The logic of attribution theory is that: (1) Faced with an outcome whose cause is not

obvious (certain), people must either draw upon the information available to them or seek new information (Carroll & Payne, 1977; Frieze, 1976a). They use the information to reduce the ambiguity (uncertainty) and to make causal inferences about the observed or reported outcome.

(2) The type of information sought is classifiable along particular task relevant dimensions.

(3) A decision about future behavior is dependent upon the location of an attribution along one of three attribution dimensions. In the context of a control system, these decisions include the assignment of responsibility for performance, variance investigation and performance standard setting.

(4) A person's conclusion about the cause (what is called the "causal attribution") is affected not only by the information used, but also by the role occupied by the actor in the task (control) process.

In summary form, the attribution process is concerned with (1) how people cope with

situations where causal relations are not obvious and (2) how this process may lead either a single actor to an incorrect conclusion or two actors to differing conclusions about the same situation.

Figure 4 presents these arguments in the control framework. One can see that nature of information utilized by either the superior or the subordinate couM affect their initial attributions. Differences in the initial attribution may affect the search process - variance investigation - and the conclusions reached. Thus, in Fig. 4, the attribution process plays a central role in the control system.

For comparison, Fig. 5 shows the model from Green & Mitchell (G-M; 1979). It is readily apparent that the two models are very similar. However the G-M model is for one actor only. The G-M model is focused on the portion of the Birnberg et al. (B-F-S) control model following the solid line from "Subordinate's Activity" to "Set Formal Budget". The "I~nk No. 1" in Fig. 5 is comparable to the "Review Prior Activity" box in B-F-S. The primary difference between the two models is that the G-M model postulates that the formation of the expectation (for the next period) will take place prior to the intervention, while B-F-S postulate that it will occur afterwards.* Thus far, this difference has been of little relevance to either research group.

The two approaches have focused up to this point on different issues. The various studies by Mitchell et al. (Green & Mitchell, 1979; Mitchell & Wood, 1980; Green & Liden, in press) have assumed knowledge of causality (i.e. they have assumed the results of 20-20 hindsight are

Performance by subordinate

Tnformotion j

Link !o.I == I Attribution by superior

Expectation for future performance

1 Link NO.2 .,

,T Superior's response

Fig. 5. The Mitchell et al. model adapted from Mitchell & Wood (1980), p. 124.

The temporal ordering between the attribution and the expectancy decision is not clear. We have unreported data which show that most subjects make the attribution first and then the expectancy; however, some subjects had the opposite ordering. Shields (1980a) reports that ~ttribution decision usually preceded the variance investigation decision which preceded the expectancy decision. Also see Ross (1977) and Weiner (1979) for the link between attributions and expectancies.


known). Based upon this knowledge they have observed the relationship between the initial attribution and the enforcement of company personnel policy, Link 2. In general, they have found that: (1) internal attributions, vis ~ vis external ones,

were made for poor performance and led to actions directed at the subordinate; and

(2) the consequences of the subordinate's act affected both the nature of the attribution and.the intensity of the superior's response; larger undesirable consequences led to internal attributions and more severe response.

The work reported in this paper focuses on the relationship between the feedback data and the initial attribution, the portion of the loop in the B-F-S model prior to that investigated by Mitchell et al. Of particular interest in the two experiments reported here is the potential for superior-subordinate conflict when they reach conflicting causal attributions.

HYPOTHESES

Information seeking A valuable step in an exploration into the

correctness of the attribution control system model is to examine the congruence between actor's information seeking behavior and com- ponents of the subordinate's activity (Fig. 3). The purpose of this step is to see whether the elements of the activity box in the model correspond to the major dimensions of the task setting about which actors desire to know more when they engage in a variance investigation.

Some attention has been devoted in the psychological literature to the development of a classification scheme to organize the information sought by people in making attributions. Much of this research has utilized an unstructured format (similar to the first experiment reported in this paper). Such a format permits the subject to specify the information desired without prior cueing (Carroll & Payne, 1977; Frieze, 1976b; Garland et al., 1975). When asked what information people would like to have (as opposed to being required to choose from a given set of data), people typically sought information about the "person" (i.e. the subordinate) performing the

task and the "task" being performed. The data about the person which was requested included information concerning his/her dispositional characteristics. The "task" (or "stimulus") information requested related to the specific characteristics of the task environment.

Support for this type of information seeking about specific task details is found in the work of Nisbett et al. (1976). s They have marshalled evidence which shows that statistical information is often ignored in making decisions and causal attributions. Hopwood (1974) also offers support in an accounting setting that managers do not use, and hence do not seek, the "statistical" information which Nisbett et al. describe as "remote, palid and abstract".

People prefer to use information for decision making which is "concrete". Nisbett et al. describe this information as "valid, salient and emotional". They speculate that the reason people use concrete information, vis d vis statistical information, to make (attribution) decisions is because of its consonance with the way in which people organize in memory information about past experience. There are four complimentary concepts of memory organization in relation to (social) decision making which also support the notion that people use qualitative, not quantitative, information to make decisions: scripts, frames, schemata and templates. (See Birnberg & Shields (1980) for a discussion of these concepts in an accounting setting.)

Consider a control example. What information does a superior seek, remember or use when inferring the causal agent(s) for a subordinate's reported behavior? The accounting answer is that the superior focuses on budgets, costs and variances - in other words, statistical information. However, if the "unstructured" information seeking experiments and the arguments by Nisbett et al. are relevant, then the superior may seek and use concrete information - e.g. interpersonal relations, physical and emotional characteristics of the subordinate, and physical properties of the task environment, etc.

These arguments support the form of our information seeking hypothesis. This hypothesis, stated in substantive form (Kerlinger, 1973), is that the data sought will be consistent with both those found in non-accounting studies and the

s Also see Taylor & Fiske (1978) and Ross (1977).


elements of the subordinate's activity in Fig. 3.

HI: The information sought by the subjects in a management control setting will fit the subordinate-task- worker trichotomy.

Causal attribution utilization The four hypotheses which are discussed in this

section focus on two issues. One is the descriptive validity o f the attribution control system model. The other is implications o f the model for control. Hypothesis Two is concerned with the descriptive validity o f the class of causal attributions managers use initially to explain behavior in a control system.

The Weiner group's (Weiner, 1972, 1974a, 1979; Weiner et al., 1971) intention was to classify (both by a priori and statistical methods) the attributions used by people to explain achievement behavior along three significant dimensions: stability, controllability 6 and location. Stability refers to the tendency of the level of a cause to be either changing or unchanging over several contiguous trials. Controllability refers to the degree o f volitional control (or influence) an individual can or cannot exert over a causal

factor. Location refers to whether the cause is internal or external to the individual performing the task. The location dimension is, in the language o f psychologists, the basis o f allocation of responsibility for a task outcome (Weiner, 1974a,b).

The results o f Weiner's research are summarized below. (1) Four causal factors are widely used to explain

achievement behavior. These are ability, effort, luck and task difficulty (Heider, 1958). Other causes are also frequently used (Frieze, 1976a,b; Weiner, 1974a). (See Table 1.)

(2) These findings in (1) above have been replicated in a variety o f settings (e.g. Carroll & Payne, 1977; Frieze et al., 1976; VaUe & Frieze, 1976; Valle & Wallendorf, 1977). The causes fit the location, stability and controllability dimensions cited earlier.

(3) There are individual differences in the use of attributions (Weiner, 1974a).

(4) People make use o f multiple attributions (e.g. both effort and ability) to explain "extreme" outcomes (Cunningham & Kelley, 1976; Kun & Weiner, 1973).

TABLE 1. A three-dimensional taxonomy of perceived causal categories relevant to the

control system

Stable Internal External

Uncontrollable Ability of superior Ability of subordinate's Background or training worker(s) of superior Task ease or difficulty Intrinsic motives

Controllable Stable effort Workers' stable effort

Diligence or laziness Ongoing job conflict

Performance measurement process

Unstable

Uncontrollable

Controllable

Fatigue

Personal, non-job related temporary problems

Effort

Response to incentives

Tight budget

Economic conditions Luck

Cooperation of workers Transitory superior- subordinate conflict Workers' unstable effort Extrinsic motives

SWeiner (1974a) originally labeled the controllability dimension as intentionality. Subsequent theoretical analysis resulted in relabellng the dimension as controllability (Weiner, 1979).


(5) There are strong indications that there is a role effect. Two people viewing the same data from different roles (i.e. superior and subordinate) make different causal attributions (Storms, 1973).

One other empirical research project applied attribution theory to examine the causal inferences managers make for accounting signals. It found that the attributions experienced managers used to explain reported performance in an experimental manufacturing setting were classifiable into the following broad categories (unreported data in Shields, 1980a): (1) people: superior and subordinate; (2) machines; (3) materials; (4) management control system; and (5) motivation.

The second substantive hypothesis, then, is intended to relate the class of attributions used initially to explain performance in a control process to those attributions used to explain achievement behavior in other task envirohments.

H2: The initial attributions used to explain reported performance in a management control process are consonant. with the class of attributions people have been found to use to explain behavior in other task environments.

The third hypothesis refers to the problem of actor-observer bias in the control task. The actor-observer bias is role induced behavior which results in the various parties using different categories of attributions (Buss, 1978; Jones & Nisbett, 1971; Bar-Tal & Frieze, 1976; Monson & Snyder, 1977; Ross, 1977; Storms, 1973; Taylor & Fiske, 1978; Wyer etal. 1977).

This discrepancy between the actor and the observer is not peculiar to laboratory studies or to attribution research. Brief et al. (1977) surveyed the field research in the evaluation literature comparing the superior's assessment of the subordinate's performance and the subordinate's self-assessment. They found little correlation between them. Of the ten studies cited (including their own), only two reported correlations above 0.5 and both of these were between 0.5 and 0.6. In contrast, all but one of the other eight studies reported correlations below 0.25. Holzbach (1978) reports similar role biases in performance evaluation.

The concept of actor-observer bias can be related to the management control setting by assuming that the reported performance of a

subordinate is reviewed by a panel of impartial observers. Assuming the reported performance could have been generated by more than one causal agent, the observers could reach different conclusions as to the "true" causal agent. When the assumption of impartiality of the observers is relaxed, the inherent role differences increase the likelihood of inconsistent causal beliefs by actor and observer. Demski (1976) was concerned with this situation arising from risk preferences and incentive schemes.

In a classic paper in this area, Jones & Nisbett (1971) report a general tendency for actors in a situation to attribute their own behavior more to external causes or to immediate influences on the situation. In contrast, observers of the actor are more likely to attribute the same behavior to factors internal to the actor. Thus, in control settings, the implication is that a superior and a subordinate may assign responsibility for the subordinate's performance to different causal agents. The superior may assign responsibility to a factor internal to the subordinate, while the subordinate may assign responsibility to a causal agent which is external. In such a case, there is a friction point in the control system.

Differences are also present for the stability dimension (Jones & Nisbett, 1971). Thus, the superior may attribute the poor work of a subordinate to that person's general pattern of diligence (stable), while the subordinate may perceive this as resulting from there not being enough to do lately (unstable). The specific hypotheses relating to the problem of role induced bias are: H3: (1) Subjects role playing the superior will use more internal initial attributions to explain a subordinate's reported performance and more external initial attributions when they role play a subordinate in a control setting.

H3: (2) Subjects role playing the superior will use more stable initial attributions to explain a subordinate's reported performance and more external initial attributions when they role play a subordinate in a control setting.

The fourth hypothesis refers to the systematic use of attributions initially to explain varying levels of performance. This hypothesis has three parts. The first part of Hypothesis four considers the notion that the use of an attribution is varied according to the magnitude of the reported performance. This is consistent with the suggestion in the literature that people do not view task


performance in a dichotomous fashion (e.g. success-failure). Rather, they recognize degrees of difference in performance. The second and third part of Hypothesis four state that people will systematically map reported performance to a set of causal agents. General support for this three part hypothesis is found in Frieze (1976a), Weiner (1972, 1974a)and Weiner etal. (1971).

H4: (1) People systematically'use an attribution to make an initial attribution for varying levels of reported performance.

H4: (2) People systematically use multiple attributions to make an initial attribution for varying levels of reported performance.

H4: (3)There are patterns in people's use of a set of attributions to make an initial attribution for varying levels of reported performance.

The final hypothesis is focused on how people respond to performances that are controlled by reference to multiple information dimensions. Specifically, how do people process information when the signals from, say, two dimensions are either unambiguous or ambiguous as to the overall quality of task performance? For example, if reported performance is favorable on units of production but unfavorable on percentage defectives, there is an ambiguous information state. Conversely, there is an unambiguous information state when units of production and percentage defectives are both either favorable or unfavorable. This is essentially the issue Barefield (1972) addressed (see also Weick, 1972, p. 269). In the context of this paper, what attributions do a superior and a subordinate initially use to explain the two information states and do the two parties use the same attributions or is this another friction point in a control system?

Intuitively, one could conjecture that unambiguous information states are more likely to be attributed to the subordinate - internal - and viewed as stable because the attributer (either superior or subordinate) has two consistent observations - the quality and the quantity dimension - upon which to base an attribution (Birnberg et al., 1977). Thus, for an unambiguous information state, stable and internal attributions would be used. Conversely, in the ambiguous information state, there may be a desire to suspend judgment, vis ~ vis the subordinate, until more data is collected. This can be done by looking elsewhere than at the subordinate (i.e. external) and by refusing to commit oneself to a stable causal agent. How long this reluctance to

commit will persist is an interesting question which we have not attempted to deal with here.

HS: (1) Internal attributions are used initially to explain unambiguous performance levels and external attributions are used initially to explain ambiguous performance levels.

HS: (2)Stable attributions are used initially to explain unambiguous performance outcomes and unstable attributions are used initially to explain ambiguous performance outcomes.

The first two hypotheses are examined in the first experiment. The third and fifth hypotheses are examined in both experiments, while the fourth hypothesis is examined in the second experiment.

DESIGN OF EXPERIMENT ONE

Sub/ects Nineteen students in a night MBA program

participated in the study. All of the subjects were enrolled in a course in business policy, which is the last course taken by students in the MBA program. Thus they had essentially completed the program. Their mean age was 31 years (SD=6) and they had a mean number of years of industrial work experience of 5 (SD=5). Overall they were a more mature and professionally oriented set of subjects than the day MBA and undergraduate populations who so often serve as subjects.

Procedure All sut~jects completed an open-ended, eight

item questionnaire. Each item consisted of a manufacturing case study. The hypothetical product being manufactured was a durable good. The eight cases presented to each subject varied along three dimensions: (1) role - superior and subordinate; (2) quality of performance - high or low; and (3) quantity of performance - high or low. In the subordinate role, subjects were to imagine they were a first line supervisor, whose primary job responsibility was the supervision of a group of factory workers. The first line supervisor's job performance was measured by the performance output of his or her group of workers. The job performance of the first line supervisor varied along the two dimensions cited above: high or low quality, and high or low quantity. In the superior role, subjects were to imagine they were a production supervisor who was the first line supervisor's superior. As before, there were four conditions for the first line


supervisor's job performance. In both role conditions, the subjects were asked

(1) what kinds of information they would want in order to assess the cause of the subordinate's reported job performance, and (2) what caused the reported performance. When the subjects were in the subordinate role, they were assessing the cause of "their" own performance level (a "self" assessment). When in the superior role, they were being asked to determine the cause of "their" subord~nate's performance (an "other" assessment).

Appendix A contains a copy of one of the eight cases. The amount of information included in each case was deliberately minimized in order to insure that a subject would be in a condition of "information incompleteness". It was necessary to provide a setting where a subject could identify a script or schemata to account for the situation but was lean with information so as to elicit the subject's attention utilization pattern for the script or schemata.

While other attribution research (Carroll & Payne, 1977; Frieze, 1976b; Garland et al., 1975; Orris et el., 1975) suggests that people are not very sensitive to order effects concerning attribution utilization, the order of presentation of the cases to the subjects was randomized in two ways: role and item sequence. The order in which the subjects played the two roles was randomized. One half of the subjects received the four superior cases first while the other half received the four subordinate cases first. Second, the sequence in which the four cases were presented within each role was also randomized for each subject.

There were at least two experimental procedures that could have been used to examine for role differences in attribution utilization. One was to have each subject occupy only one role. In this case, the role variable would be a between-subjects factor. An advantage of this procedure was that each subject supposedly had his role established while performing information processing. A disadvantage was that the experimenter had no assurance that any obtained role differences were due to differences in a person as he occupied each role. Instead, the obtained differences may have been attributable to interperson factors. The second procedure that could have been used was to have each subject occupy each role. A possible disadvantage of this approach was a "carry-over" effect from one role to the next role. Randomiza- tion of role order across subjects tended to reduce

this possible disadvantage. An advantage of the latter procedure was that obtained role differences were attributable to intraperson differences as the person occupied both roles. The choice of approach would appear to be dictated by whether the data analysis uses a between subject or within subject approach.

RESULTS OF EXPERIMENT ONE

The subjects' responses to each case were tabulated separately. There were two types of responses per subject for each of the eight cases: information seeking and attributions used. Before any results are discussed, the manner in which the data were coded is described.

Coding o f data The information seeking data were coded after

an extensive study of the actual responses. The method of coding was influenced by the discussion in Glaser & Strauss (1967). They do not outline a specific method but, instead present a general approach to content analysis of qualitative data. The data were read and then categories were developed which included most of the requests. Then each datum was coded by one coder as to which category it was a member. Other studies have coded information seeking data in similar fashion (Carroll & Payne, 1977; Frieze, 1976b; Garland et al., 1975).

Eighteen months later, the same coder blindly recoded about 20% of the information seeking data. The intra.coder reliability was about 90%. Overall, 90% of the data was classifiable into one of eight specific categories. This coding process resulted in the following categories; the frequencies are reported in Table 2. (1) Task process: information about the charac-

teristics of the production process and working conditions.

(2) Equipment-machinery: information about the age, condition and efficiency of the equipment.

(3) Standard-performance measures: realism of rates, trends over time, and comparison to other groups.

(4) Factors external to the firm: supply of raw materials and union relations.

(5) Upper management orientation: goals, objec- tives and quality-quantity tradeoffs.

(6) Subordinate's characteristics: education, train-

A T T R I B U T I O N S , C O G N I T I V E P R O C E S S E S A N D C O N T R O L SYSTEMS 79

T A B L E 2. F r e q u e n c y o f the classes o f i n f o r m a t i o n sought

Classes Both of information Subordinate Superior roles

HH* HL LH LL Total % R HH HL LH LL Total % R Total %

1. Task process 2. Equipment 3. Standards-performance

measures 4. Faetors external to

the fkm 5. Upper management 6. Subordinate 7. Workers 8. Subordinate-worker

relationships

Totals

10 8 7 10 35 11 4 7 9 8 10 34 11 5

20 14 18 11 63 20 2

1 5 2 3 11 4 8 3 8 7 5 23 8 6 5 7 10 16 38 12 3

21 23 19 32 95 30 1

2 3 4 4 13 4 7

69 77 75 91 312 100

9 13 10 10 42 12 4 77 11 6 5 4 8 23 6 7 57 8

18 18 17 14 67 18 2 130 19

5 7 5 8 25 7 5 36 5 2 6 10 6 24 7 6 47 7

29 23 31 24 107 29 1 145 22 14 15 12 16 57 16 3 152 23

6 4 4 6 20 5 8 33 5

89 91 93 92 365 100 677 100

*First letter = quality; second letter = quantity; H = high; L = low; R = rank.

T A B L E 3. F r e q u e n c y in the use o f causal a t t r i b u t i o n ca tegor ies*

Causal attributions

Subordinate Superior Both roles

Total Total Total HF HL LH LL No. % HH HL LH LL No. % No. %

1. Subordinate's ability 2. Subordinate's effort 3. Subordinate's stable

e ffor t 4. Subordinate's mood 5. Subordinate's intrinsic

motives 6. Subordinate-worker

interaction 7. Workers' personalities,

backgrounds, interests 8. Workers' motives 9. Workers" unstable help

and effort 10. Workers' stable help/

hurt 1 I. Ability-task interaction 12. Task 13. Luck 14. Extrinsic motives

2 0 1 3 6 5 8 3 2 11 24 15 30 10 7 4 3 7 21 17 9 4 4 9 26 16 47 16

1 0 0 0 1 1 4 I 0 0 5 3 6 2 1 0 0 0 1 1 1 0 0 1 2 1 3 1

3 3 2 4 12 9 4 7 6 1 18 11 30 10

4 1 0 3 8 6 3 1 1 4 9 6 17 6

3 5 4 1 13 10 5 2 1 3 11 7 24 8 1 1 0 0 2 2 3 0 1 0 4 2 6 2

1 1 3 3 8 6 2 0 2 1 5 3 13 4

1 0 1 1 3 2 3 0 0 2 5 3 8 3 1 0 0 2 3 2 2 0 1 0 3 2 6 2 5 7 3 10 25 20 5 9 4 9 27 16 52 18 2 II 0 0 2 2 0 0 0 0 0 0 2 I 4 8 8 2 22 17 2 9 13 0 24 15 46 16

Total codeable 36 30 25 36 127 100 51 36 35 41 163 100 290 100t Uncodeable 4 6 7 8 25 3 3 5 5 16 41

Totals 40 36 32 44 152 54 39 40 46 179 331

*For code, see Table 2. t Rounding error of 1%.


ing, experience, remuneration and leadership style.

(7) Workers' characteristics: education, training, experience, job attitude and remuneration.

(8) Subordinate-worker relationship. (9) Unclassifiable.

The coding of attributions was performed in a similar fashion. The method of coding was based on discussions contained in Elig & Frieze (1975, 1979). Elig & Frieze (1975) detail how to identify how an attribution is to be classified and to what specific part of a dimension it belongs (for example, stable or unstable). They give many illustrations of how to code, for example, based on the syntax and the semantics of the datum, and the perspective of the subject in writing the response. This general method of coding open- ended attribution data has been used successfully elsewhere (e.g. Carroll, 1978; Carroll & Payne, 1977; Frieze, 1976b; Mitchell & Wood, 1980; Smith & Hunt, 1978; VaUe & Wallendorf, 1977).

The attribution categories and their frequencies are reported in Table 3. In this case, one coder was used to classify the attributions. Eighteen months later, the same coder blindly recoded about 20% of the data. The intra-coder reliability was about 85%. Overall, 88% of the data was codable into one of 14 specific categories of attributions in Table 3.

Information seeking In Table 2, the responses of the subjects

classified into the eight categories by the two roles are presented. The responses fit the three aspects of the subordinate's activity model found ia Fig. 3 - subordinate, task and workers. In this simulation of the management control process, 38% of the requests were for the task information - classes one, two and three in Table 2. Information seeking about the workers (Class 7) accounted for 23% of all requests. Twenty-two per cent of the information requests were for information about the subordinate. In total, in this study 83% of the classifiable information seeking requests were for information about the task, the subordinate and the workers. Thus, while no formal test was used to measure how good the 83% value was, it seemed reasonable to conclude that this was a good fit to the model's categories. Thus, the first hypothesis was not rejected.

Looking at the entire list of information requests, there were similarities in the rank of requests between roles. A Spearman's rank

correlation between the two roles, 0.71 (p = 0.07), was marginally significantly different from zero. Thus, there is basis for continuing to pursue the idea that subjects request similar patterns of information independent of the role they occupy.

Causal attribution utilization Next attention is given to the question of

whether the initial causal attributions made in a control setting were similar to those found in other attribution research. Specific causal categories are shown in Table 3. When the responses for all the conditions were combined, the most frequently cited cause of performance was the specifics of the task. The subordinate's effort and extrinsic motives tied as the second most frequently cited causes.

An examination of Table 3 shows that in drawing causal inferences, the subjects used some categories more than others. Eight of the 14 causes (task, subordinate's effort, extrinsic motives, subordinate's ability, subordinate's intrinsic motives, workers' personalities, backgrounds and interests, subordinate-worker interaction, and worker's help and effort) constituted 88% of all the codable attributions made. This group of attributions was similar to ones used in the other accounting study cited earlier and in the nonaccounting task settings. Consequently, Hypothesis two was not rejected.

In this experiment, the attributions were made after reading the performance data; thus they represent the initial attribution shown in Fig. 4. This was the superior's first assessment of the subordinate's performance and the subordinate's first assessment of his or her own performance after reviewing the performance report. In a control setting, these attributions would control whether either actor considered an investigation desirable and, if one was, what was the most likely cause or set of causes to serve as a starting point in the investigation.

In this regard, Hypothesis three suggested that the superior and the subordinate would use different initial attributions. This could have been observed in one of two ways. The rank order in the frequency of use of the various attribution categories between roles could have differed. This would have indicated a markedly different view of the world by the subjects as they occupied each role.

Alternatively, the pattern of frequencies might have shifted between roles but not enough to have


shifted the relative rank o f the various attributions. This would have suggested a less drastic disagreement between roles. While the former would have been desirable to not reject the third hypothesis, in view o f the limits o f role playing and the exploratory nature o f this research, the latter was a more realistic expectation given the limitations o f the intra-subject design discussed earlier.

An inter-role Spearman rank correlation for the total frequencies in Table 3 o f 0.85 (p<0.001) was obtained in comparing the frequency in the use o f various perceived causes by the sub/ects as subordinates to those perceived causes used by the same sub/ects when they role played the superior. Thus subjects within this control process tended to use the same attributions, in a rank order sense, in each role.

However, there were some role differences as suggested by Hypothesis three in the frequency in the use of attributions. For example, when considering the location dimension, collapsing the data across the intra-subject role variable, attributions about the performance o f the subordinate were more internal (external) when the subjects were role playing the superior (subordinate)(X 2 = 10.5, d.f. = 1, p < 0.005) (see Table 4). In addition, when considering the stability dimension, there were more ascriptions to stable

(unstable) causes in the superior (subordinate) role (X 2 = 6.26, d.f = i, p < 0.02) (Table 4). Thus, both parts o f Hypothesis three were not rejected using the weaker test.

The final set o f data to be reported in this section considered those cases where the two variances reported were o f opposite signs (Hypo- thesis five). Unlike those instances where both variances were of the same sign, ambiguity was present. Ambiguous outcomes were hypothesized to be ascribed either to external or to unstable causal factors, while unambiguous outcomes were ascribed either to internal or to stable factors. Operationally, an outcome was unambiguous when the quality and the quantity performance dimensions were consistent (e.g. high quantity and high quality). Conversely, an outcome was ambiguous when the two variances were conflicting (e.g. high quality and low quantity).

To test the two parts of the hypothesis, two chi-square tests were performed. Note that the two roles were combined in these tests. The first chi-square (a 2X2 design) was outcome ambiguity level and location (internal or external). The frequency counts for the 2X2 table were based on the data in Table 4. The data were not inconsistent with the first part of the fifth hypothesis. Internal attributions were more frequently used to explain unambiguous outcomes (79 vs. 42), while external

TABLE 4. Frequency in the use of the causal attribution dimensions*,t

Causal Subordinate Superior attribution dimensions HH HL LH LL Total HH HL LH LL Total

StabflRy: Stab~ 13 7 7 14 41 24 12 11 20 67 Unstable 21 22 19 22 84 22 20 27 18 87

Totals 34 29 26 36 125 46 32 38 38 154

Location: Internal t2 6 5 15 38 25 16 15 27 83 External 18 22 22 17 79 18 20 23 15 76

Totals 30 28 27 32 117 43 36 38 42 159

Controllability: Uncontrollable 19 13 9 21 62 22 15 11 30 78 Mediate 3 2 0 4 9 4 3 3 1 11 Controllable 15 14 ,, 16 10 55 17 18 22 9 66

Totals 37 29 25 35 126 43 36 36 40 155

*For code see Table 2. ~fThe frequencies reported are based on the frequencies reported in Table 3. The causal categories in Table 3 are classif'mble into the stability, location and controllability framework in this Table. The classification system is based on Elig & Frieze (1975), Frieze (1976b) and Weiner (1979).

82 MICUAEL D. SHIELDS, JACOB G. BIRNBERG and IRENE HANSON FRIEZE

attributions were used more frequently to explain ambiguous outcomes (87 vs. 68). The differences were significant (×2 = 12.5, d.f = 1, p < 0.001) and in the hypothesized direction.

The second part of the fifth hypothesis focused on the outcome ambiguity level by stable-unstable attribution utilization. The results of the 2X2 chi-square analysis showed stable attributions were used to explain unambiguous outcomes (71 vs. 37), while unstable attributions were more frequently used to explain ambiguous outcomes (88 vs. 83). The differences were as hypothesized and significant (X 2 = 7.9, d.fi = 1, p < 0.005).

All four hypotheses examined in the first experiment were not rejected. The types of information sought to explain performance and the categories of attributions used were not inconsistent with the first two hypotheses. The actor-observer bias in attribution usage was found which was not inconsistent with Hypothesis three. Finally, the attributions were utilized differently depending upon whether the reported performance outcome was ambiguous or not. The second experiment was intended to examine further the actor-observer bias, the systematic use of a set of attributions, and the use of attributions to explain reported performance of varying levels of ambiguity.

DESIGN OF EXPERIMENT TWO

Subjects Ninety-six day MBA students enrolled in a day

business policy course at the same university participated in this experiment. All of the subjects were in their final term of the MBA program.

Procedure The subjects were asked to make initial

attributions based on a case. There were 16 different variations to the basic case. Two of the variations resulted from the role the subject was asked to play: subordinate, labeled the first line supervisor, or the superior, labeled the second level supervisor, who was to evaluate the first line supervisor. The quantity of production in the cases was set at one of four levels and the quality of production was set at one of two levels. Thus, there were two role levels X four quantity levels X two quality levels. The subjects were randomly assigned to one and only one of the 16 variations with six subjects in each cell.

The four levels for the quantity variable were set using a normal distribution with a mean of 150,000 units and a standard deviation of 5000. The four levels were set so that on a normal distribution the areas to the left of the production level were 0.1, 0.33, 0.66, and 0.9. This generated production levels of, respectively 143,600, 147,850, 152,150 and 156,400 units. The two quality levels were set at 0.1 and 0.9, or a percentage sampled defectives of 2.72% and 5.28%, from a normal distribution with a mean of 4% (S D = 1%). In the cases presented, the "actual" data for the subordinate for the previous five years were adjusted so as to be slightly off of the mean and standard deviation. This was done so that the past performance of the subordinate was "psycho- logically" different from the group of subordinates' past performance (the mean and standard deviation), although the "statistical" difference was nil. All 16 cases included exactly the same background statistics.

The subjects were asked to make an initial attribution for the performance of the subordinate. The attribution response sheet contained ten 9-point scales. This method of attribution- measurement was common (Elig & Frieze, 1979). All the scales were anchored at the ends by labels such as "high", "low", "lack", "extreme", etc., with each mid-point labeled "no-influence". These causal attributions were included based on the subjects' responses in experiment one (Table 3). The ten scales were: task, subordinate's effort, subordinate's leadership ability, subordinate's decision making ability, subordinate's intrinsic motivation, extrinsic motives, subordinate-worker cooperation, workers' effort, workers' ability and validity of the production measurement process.

Appendix B contains a sample copy of one of the 16 cases. As in experiment one, the amount of information in the cases was minimized to insure a situation of "information incompleteness". However, in the second experiment, "more" information was provided than in the first experiment; thus the former experimental setting was not quite as lean as the latter one.

RESULTS OF EXPERIMENT TWO

The first data to be reported continue the investigation of the actor-observer bias of Hypothesis three. Specifically, we were concerned with the presence of any actor-observer bias on


TABLE 5. Actor-observer bias in attribution usage: internal vs

external*

83

Attribution type

Role Internal External t t

Superior X 1.43 1.18 2.35 (observer) SD 0.71 0.56 (p < 0.02)

Subordinate X 1.03 1.23 2.16 (actor) SD 0.53 0.77 (p < 0.02)

*The means in the table were calculated based on linear combinations of the internal and the external attributions for each subject. The amount of each attribution, for each subject, is the absolute difference of an attribution response from the mean response for the 48 subjects in that role condition. See the note in Table 8 for the scale properties of each attribution. For each subject, the total absolute value of the internal and the external attributions used was calculated by summing across the absolute amount of each individual attribution. Then each subject's total response was used to calculate a group mean internal and external attribution usage for all 48 subjects in the same role condition. ~'A one tailed t-test was used to test for significance.

the location and stability dimensions. To test for asymmetric attribution use on the location dimension, linear combinations o f those attributions classified by Elig & Frieze (1975) as internal and as external were formed. In this case, the internal attributions were the subordinate's effort, leadership ability, decision making ability and intrinsic motivation. The external attributions were task, extrinsic motivation, workers' effort and ability, and validity of the measurement process. See Note 1 in Table 5 for details about how the linear combinations were formed. The actor-observer bias specified the direction o f difference for the two means. Thus, a one tailed t-test was used to test for the actor-observer bias. 7 In the superior role (the observer), the subjects ascribed the subordinate's performance more to internal causes than to external causes (t47 = 2.35, p < 0.02). Conversely, those subjects in the

subordinate role (the actor) ascribed the same performance more to external causes than internal causes (t47 = 2.6, p < 0.02). See Table 5.

No systematic inter-role asymmetric use of stable and unstable attributions was found. Rather, it is interesting to note the subjects in each role condition attributed the performances more to stable than unstable causes. The linear combinations were formed as they were f ~ the internal-external analysis of the actor-observer bias. s See Table 6 for details. In the subordinate role, the subjects used more stable attributions than unstable attributions (t47 = 7.79, p < 0.001). Similar results were present for the superior role (t47 = 7.5, p < 0.001). Thus, in contrast to the first experiment where both parts Of the hypothesis were not rejected, significant hypothesized differences were found on the location dimension but not on the stability dimension in the second

7 Before the tests were performed, both Hartley's and Cochran's tests of homogeneity of variance were performed for each of the ten attributions by the 16 cells (Kirk, 1968, p. 63). All of the 320 tests (2 test methods × 16 cells × 10 dependent variables) showed acceptable levels of heterogeneity of variance as allowed for by the two tests. In addition, inspection of skew and of kurtosis statistics for the 160 cases (10 × 16) showed that there are two cases where the skew is greater or less than +1 or - 1 (where 0 is normalcy) and 13 cases where the kurtosis is greater or less than +1 or - 1 (where 0 is normalcy). However, considerable analytical evidence is available which indicates that such departures from normality have very little effect on either the level of significance or the power of the fixed effects model F-test (Glass etal., 1972; Kirk, 1968).

s See Note 7.


TABLE 6. Actor-observer bias in attribution usage: stable vs

unstable*

Attribution type

Role Stable Unstable tt

Superior X 5.96 2.83 7.50 (observer) SD 3.03 1.50 (p < 0.001)

Subordinate "X 5.19 2.63 7.79 (actor) SD 2.68 1.31 (p < 0.001)

*The means in the table were calculated based on linear combinations of the stable and the unstable attributions for each subject. The amount of each attribution, for each subject, is the absolute difference of an attribution response from the mean response for the 48 subjects in that role condition. See the note in Table 8 for the scale properties of each attribution. For each subject, the total absolute value of the stable and the unstable attributions used was calculated by summing across the absolute amount of each individual attribution. Then each subject's total response was used to calculate a group mean stable and unstable attribution usage for all 48 subjects in the same role condition. tA two tailed t-test was used to test for significance.

experiment. Next, the data were examined for systematic

use of a set o f at tr ibutions to explain varying levels Of reported performance - the three parts of Hypothesis four. Significant F-ratios in analysis o f variance (ANOVA) were used to infer systematic use o f the ten attributions. 9 Table 7 presents the results of the ANOVA for each attr ibution. Table 8 presents the means and standard deviations of the attr ibutions used to explain each of the levels of performance in the 16 cases. As is shown, most of the attributions in Table 7 were significant On the quant i ty and/or the quality o f variables. This indicated that the subjects had made systematic use o f an at tr ibution to explain varying levels of performance in a between-subjects design. This result did not reject the first part o f the hypothesis . •

A casual examination of the means in Table 8 indicated that the pattern of at tr ibution use appeared to be in what was, intuitively, the proper direction. For example, the means of those items related to the subordinate 's job skills increased with the quality of performance (see subordinate 's effort, ability and leadership). Conversely, poor performance was related to the task and the

scheme o f extrinsic motivators. Given the exploratory nature of the exercise, these responses appeared reasonable.

To examine for systematic use of multiple attr ibutions for differing levels of quality and quanti ty of performance, a multivariate analysis of variance (MANOVA) was performed. As shown in Table 9, the quanti ty ( F = 1.93, p < 0.005) and quality ( F = 5.01, p < 0.001) variables were highly significant. Thus, the subjects appeared able to use multiple attr ibutions systematically to explain varying levels o f performance. This result did not reject the second part of Hypothesis four.

Patterns in the use of at tr ibutions to explain varying levels of performance were ascertained by factor analysis. The factor analytic solution was subjected to varimax rotat ion to aid interpreta- tion. For purposes of interpreting the rotated factors in Table 10, loadings of 0.6 or more were used to identify elements of the factors. The elements were underlined in Table 10.

Three factors were extracted which together account for approximately 71% of the total variance. These factors were labeled "worker" (46%), "mot ivat ion" (13%) and "measurement process" (11%). An examination of Table 10

9 See Note 7.

A T T R I B U T I O N S , C O G N I T I V E P R O C E S S E S A N D C O N T R O L S Y S T E M S 8 5

T A B L E 7. A n a l y s i s o f v a r i a n c e : c ausa l a t t r i b u t i o n s

Subordinate

Subordinate- Validity of Source of Decision Extrinsic worker Workers' Workers' measurement variation Task Effort Ability making ability Motivation motivation cooperation effort ability process

Quantity (QN) 2.93"~ 11.51 § 5.59# 7.23 ¶ 2.87t 6.87 ¶ 8.23 ¶ 12.12 ¶ 2A4 0.70 Role (R) 1.17 1.44 3.49* 2.51 1.79 1.69 1.82 2.35_ 0.09 0.29 Quality (QL) 1.60 18.03 ¶ 25.50 ¶ 26.83 ¶ 0.27 0.52 23.50 ¶ 31.0411 23.35 ¶ 3.58* QN × R 0.93 2.901 1.50 0.19 0.23 1.04 1.40 0.49 0.15 0.54 QNx QL 0.62 1.00 1.18 0.52 1.94 3.01# 4.48"~ 2.791 1.69 0.71 R X QL 0.29 0.78 0.58 " 0.52 3.50* 0.02 0.31 0.0l 0.09 0.46 QN x QL x R 0.49 0.11 0.32 0.57 3.871 1.95 0.43 0.44 0.47 0.65

Degrees of freedom: 1,80 for Role, Quality, Person × Quality; 3.80 for all other effects. *p < 0A;? p < 0.05;~ p < 0.01; § p < 0.001; ~l p < 0.0005.

T A B L E 8. V a l u e s o f t h e a t t r i b u t i o n s f o r t h e levels o f t h e r e p o r t e d p e r f o r m a n c e

Factor title

~ evel

Attributions

(Percentage ....... Quanti ty (units produced) Quality defectives)

143,600 147,850 152,150 156,400 2.72% 5.28% Subordinate Superior (actor) (observer)

Task X 5.8 5.0 4.9 5.0 5.0 5.3 5.3 5.0 SD 0.9 0.9 1.1 1.4 1.3 1.0 0.9 1.3

Subordinate's effort X 5.0 4.8 6.1 6.6 6.2 5.1 5.8 5.5 SD 1.3 1.5 1.2 1.5 1.3 1,6 1.5 1.7

Subordinate's leadership X 4.8 4.7 5.6 6.2 6,1 4.6 5.6 5.0 ability SD t .7 1.7 1.7 1.6 1.6 1,6 1.6 1.8

Subordinate s decision making X 4.5 5.0 5.7 6.3 6.1 4.6 5.6 5.1 ability SD 1.8 1.4 1.5 1.6 1.5 1.5 1.6 1.7

Subordinate's intrinsic motives X 5.2 5.6 4.8 4.4 4.9 5.1 4.8 5.2 SD 1.4 1.2 1.6 2.1 1.7 1.6 1.6 1.7

Extrinsic motives X 5.4 5.6 4.8 4.0 4.8 5.0 4.8 5.1 SD 1.7 1.1 1.3 1.7 1.6 1.6 1.6 1.6

Subordinate-worker X 4.9 5.3 6.3 6.5 6.4 5. l 5.9 5.6 cooperation SD 1.8 1.3 1.3 1.6 1.5 1.5 1.6 1.6

Workers' effort X 4.7 4.6 6.0 6.4 6.1 4.7 5.6 5.2 SD 1.7 1.4 1.2 1.5 1.4 1.6 1.6 1.7

Workers' ability ,~ 5.2 5.3 5.6 5.0 6.0 5.0 5.5 5.5 SD 1.3 0.9 1.2 1.0 0.9 1.1 1.1 1.1

Validity of the measurement X 4.7 4.8 5.0 5.3 5.3 4.7 4.9 5.1 process SD 1.7 1.3 1.5 1.4 1.4 1.5 1.3 1.6

For the ten 9-point scales used to measure the intensity o f at tr ibution utilization, the left anchor of each scale is assigned the numerical value of one. The means and standard deviations were calculated as follows: there are 16 cells to this design (4 quanti ty × 2 quality × 2 role). The statistics reported for any level of a factor are averaged across all levels o f the other two factors.


TABLE 9. Multivariate analysis of variance: causal attributions

Source of variation d.f. F

Quantity (QN) 30,209 1.93t Role (R) 10,71 0.64 Quality (QL) 10,71 5.01~ QN X R 30,209 1.22 QN × QL 30,209 1.68" R × QL 10,71 0.87 QN X R × QL 30,209 0.95

*p < 0.05; tp < 0.005; ~p < 0.001.

In total, all three parts to Hypothesis four were not rejected.

The last data to be presented were to test Hypothesis five. This hypothesis concerned the differential use of attributions as the level of outcome ambiguity was altered. Ambiguous outcomes were operationalized as an inconsistency between quality and quantity of output: largest output (156,400) and largest per cent defectives (5.28) or lowest output (143,600) and lowest per cent defectives (2.72). Unambiguous outcomes

TABLE 10. Factor analysis on causal attributions

Factors

Causal attribution 1 2 3

1. Task -0.11400 -0.05055 0.01572 2. Subordinate's effort 0.40403 -0.17933 0.18903 3. Subordinate's leadership

ability 0.31247 -0.14562 0.13408 4. Subordinate's decision

making ability 0.28244 -0.21782 0.13886 5. Subordinate's intrinsic

motivation -0.07024 0.90511 0.04380

6. Extrinsic motivation -0.20098 0.82156 -0.09939

7. Subordinate-worker cooperation 0.84611 -0.05367 -0.00550

8. Workers' effort 0.80289 -0.28017 0.00975

9. Workers' ability 0.64970 -0.11321 0.43027

10. Validity of the production measurement process 0.06879 -0.00757 0.95184

Eigen values 4.64 1.37 1.09 Per cent variance 46.49 13.27 10.89

shows that factor three, measurement process, consists of only a single component. The worker factor contained the attributions of workers' effort and ability and subordinate -worker cooperation. The motivation category consisted of both intrinsic and extrinsic motivation. These factors coincided with a classification scheme based on elements of the attribution theory based management control process (Fig. 4).

In addition to these three factors, the next two factors generated by the analysis, but having eigen values less than one, were also consistent with Fig. 4. These factors could be labeled "task" and "subordinate". While the former consisted solely of the task attribution, the latter consisted of the subordinate's effort, leadership ability and decision making ability.

were: largest output and smallest per cent defectives or lowest output and highest per cent defectives. Linear combinations o f attributions classified as internal, external, stable and unstable were generated as described earlier (see Table.s 5 and 6).

Inspection o f Tables 11 and 12 indicated that there were no significant differences in the means for the cue ambiguity factor. Thus, the null hypotheses could not be rejected. Consequently, Hypothesis five was rejected.

In summary, in the second experiment, further support was found for the actor-observer bias on the location dimension. Subjects were found to use a set o f attributions in a systematic fashion. In contrast to the managers who served as subjects in experiment one, the student subjects' use of


TABLE 11. Cue ambiguity by role for two attribution dimensions

87

Cue ambiguity

Ambiguous

Unambiguous

Location

Internal External

Role Role

Cue Subordinate Superior ambiguity Subordinate

0.97 1.27 1.12 Ambiguous 1.31

1.20 1.70 1.45 Unambiguous 1.55

1.09 1.49 1.29 1.43

Superior 1.17

1.45

1.31

1.24

1.50

1.37

Stability

Stable Unstable

Role Role

Cue Cue

ambiguity Subordinate Superior ambiguity Subordinate Superior ambiguous 6.05 7.06 6.56 ambiguous 3.45 3.01

Unambiguous 4.92 5.85 5.39 Unambiguous 2.74 2.57

5.49 6.46 5.98 3.10 2.79

3.23

2.66

2.94

Cell entries are linear combinations of attributions. See Tables 5 and 6 for details. There are 12 data points used to estimate each cell mean: two performance outcome conditions with six subjects each in each condition.

TABLE 12. Analysis of variance on cue ambiguity by role for two attribution dimensions

Sum of Mean Source squares d.f. square F Probability

Internal Role (R) 1.93 1 1.93 4.12 < 0.05 Cue ambiguity (CA) 1.30 1 1.30 2.78 > 0.1 R X CA 0.12 1 0.12 0.26 > 0.6

External Role (R) 0.16 1 0.16 0.27 > 0.5 Cue ambiguity (CA) 0.84 1 0.84 1.42 > 0.2 R × CA 0.00 1 0.00 0.01 > 0.9 Error term 25.91 44 0.59

Stable Role (R) 11.19 1 11.19 0.98 > 0.3 Cue ambiguity (CA) 16.36 1 16.36 1.44 > 0.2 R X CA 0.02 1 0.02 0.00 > 0.9 Error term 501.49 44 11.40

Unstable Role (R) 0.98 1 0.98 0.50 > 0.4 Cue ambiguity (CA) 3.83 1 3.83 1.95 > 0.1 R × CA 0.17 1 0.17 0.09 > 0.7 Error term 86.44 44 1.97


attributions in experiment two did not show the actor-observer bias on the stability dimension; nor did they respond to a significant degree to the ambiguity present. Thus, there were some conflicting findings between the two studies. They may be ascribable to differences in the subject's experience.

DISCUSSION

This section has two parts: discussions of the results of the two experiments in relation to the five hypotheses and the limitations of the analyses contained in this paper.

The first hypothesis stated that the classes of information sought to explain performance in a management control setting would fit the subordinate -task-worker trichotomy of the activity box in the attribution control system model (Fig. 3). From the first experiment, the information seeking was not inconsistent with the trichotomy. Over 80% of the coded requests were for information about task, subordinate, and workers. In addition, the types of information sought by the subjects did not significantly vary by the role occupied. Notably, concrete information, not statistical information, was most sought to explain performance.

The second hypothesis stated that the initial attributions used to explain performance in a management control process were consonant with the categories of attributions (e.g. ability, effort, or task, etc.) people have been found to use to explain behavior in other task and control settings. The data was not inconsistent with the hypothesis.

The third hypothesis considered different attribution usage with respect to the actor- observer bias. Both experiments reported in this paper found that the actor-observer bias was present on the location dimension. In addition, manager subjects exhibited it on the stability dimension as well. These results may be of importance to control theorists in that they indicate that superior-subordinate friction over the assignment of responsibility for task performance may be an inherent characteristic of control systems due to people's psychology. The issues for accountants are then (1) how to generate feedback reports which reduce this friction point, and (2) if (1) is not possible or desirable, how to structure behavior in control systems so as to smooth out the friction.

The fourth hypothesis concerned people's systematic use of attributions to explain varying levels of performance. Three sub-hypotheses were formed, which respectively considered people's systematic use of (1) a single attribution, (2) multiple attributions and ( 3 ) a group of attributions, to explain varying levels of reported performance. In the second experiment, the subjects did systematically use the attributions as specified by the three parts of the fourth hypothesis. The subjects did systematically use both single attributions and multiple attributions to explain different levels of performance that varied along two dimensions (quantity and quality). Finally, the subjects systematically used the group of attributions in a pattern that is interpretable in terms of elements of the attribution theory based management control process. These five elements are the subordinate, the workers, the task, motivation and the measurement process.

Both parts of the fifth hypothesis, focused on attribution usage by cue ambiguity, were not rejected by the data in the first experiment. However, in the second experiment the effects were not present. These results about how people cope with uncertainty were exploratory and further research should be encouraged. As Barefield (1972) suggested, how managers cope with ambiguous information states is of concern to • accountants because of the desire to maintain an efficient control system with minimal amounts of friction present in it.

Limitations of the studies These two experiments are intended to be

exploratory. As such, their limitations are both those of laboratory studies and of experiments which are intended to initiate a line of research rather than contribute to a well defined body of prior research. The former limitations include the issues of subject surrogation, role playing and the ability to entrap in the laboratory the critical dimensions of a task setting. However, it should be noted that the subjects selected for Experiment one were practicing managers. As such, they brought to the task setting certain desirable experiences and skills that students do not always possess.

The exploratory nature of the studies is reflected in the relevance of the hypotheses investigated as required first steps prior to a systematic study of the variance investigation


decision itself. While one could have begun research with the type of issues raised in the next section of this paper, the limited prior work with attribution theory in simulated business settings raised questions about the advisability of initiating research by performing such studies.

One added caveat must be raised. These experiments deliberately minimized the amount of information possessed by the subjects concerning the activity being reported relative to that available in many job settings. Clearly, such data must become available to subjects as research progresses even in the case of laboratory studies. This is needed so that the interaction between the attribution process as a set or predisposition and the available data can be examined.

FUTURE RESEARCH DIRECTIONS

Viewed in the form of the management control diagram found in Fig. 4, the focus of these two experiments has been on the initial phase of the feedback process. Based upon feedback reports, what information do people seek and, prior to receiving these data, what attributions do they initially make? Both of these questions are relevant to accounting and managerial accountants. The former suggest the kind of information both superior and subordinate are likely to seek or will desire to have available to them. The second suggest that actors may enter the investigation process with potentially differing points of view. Since no data were actually supplied to the subjects, there is no way of ascertaining whether different initial attributions result in different conclusions (final causal attributions) or if the investigation process will lead them to converge.

It is, in fact, still an open question as to when an actor will decide to investigate. Stated in attribution terms, do certain initial causal attributions lead to a decision to investigate, whereas, ceteris paribus, others do not?

In substance, what the exploratory studies reported here suggest is that information which will be sought by superiors and subordinates is similar. These--data will come_ from accounting reports and memory of the superior or sub-

ordinate. These data may modify the actor's initial attribution so that each will decide upon a likely cause for the reported behavior. Unless the data generated routinely or as a result of an investigation are able to resolve any disparity in initial causal attributions, the actor-observer bias may lead to different final conclusions (including assignment of responsibility) as to why things went wrong or, alternatively, why they were so good. This in turn could result in superior- subordinate friction.

It would appear that the experiments reported here support the original intent of the studies - to begin the systematic study of the use of feedback information within the framework suggested by Birnberg et al. (1977). The studies raise several important research issues for management control. One is the issue of whether the investigation process will serve as a source of convergence or divergence between superior and subordinate. This would appear to be a most appealing area for further research. To get at that topic, however, researchers probably will have to work through a series of research projects. Future research would productively focus on the role effects and the ambiguity effect which are the tendencies of the two actors to utilize different causal attributions to explain ambiguous and unambiguous performance which is reported.

Another focus for future research is those control settings where a series of events are related t o each other. The act of attribution is nontrivial in attempting to sort out the influence of each event to a chain of events. For example, in the cases used in these experiments, the poor quality of performance could be related not only to the manner in which the production department did its job, but also to the manner in which the purchasing department performed its job. That, in turn, could be related in part to shortages in the external market. However, no one factor is obviously responsible. Research on non-accounting tasks has shown that exactly how these events are

sequenced in the mind of the evaluator affects decisions (Brickman et al., 1975). Since accounting reports are a significant link in the communication of these events, they may affect the manner in which both the causal chain is constructed and subsequent control decisions.


B I B L I O G R A P H Y

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91

APPENDIX A

Sample o f a stimulus for Experiment one

Imagine you are a production supervisor at a manufacturing plant. Your primary job responsibility is the supervision of a group of first-line supervisors. One of these first-line supervisor's primary job responsibility is the supervision of a group of factory workers who assemble durable goods. Suppose this first-line supervisor's job performance (as measured by the production of this supervisor's subordinates) is of a low quality (percentage defectives) and a high quantity (units of production).

(A) What kinds of information would you want in order to assess the cause(s) of this first-line supervisor's job performance?

(B) Why do you think this first-line supervisor performed in this manner?

92 MICHAEL D. SHIELDS, JACOB G. BIRNBERG and IRENE HANZON FRIEZE

APPENDIX B

Sample of a stimulus for Experiment two

Imagine you are a second-level supervisor whose primary job responsibility is the supervision of a group of first-line supervisors. Each first-line supervisor's primary job responsibility is the supervision of a group of production workers who assemble household durable goods at a large manufacturing plant. Periodically you assess the job performance of each of these first-line supervisors. Before each operating period, all first-line supervisors are expected to present to you their proposal for their respective group's next period's performance goals as part of the budget process.

One of these first-line supervisors is a "typical" first-line supervisor (in relation to his or her peers) in terms of education, experience, age, and past performance. In the past this first-line supervisor has experienced good working relations with members of his or her production group.

Management assesses the job performance of first-line supervisors by two output measures: units of production and percentage of sampled defectives. For the last five years (XI to X5), the performance of this first-line supervisor's group and other similar groups has been:

This first-line Other supervisor's group groups

Units of production: Mean 149,973 150,025 SD 5004 4995

% Sampled defectives: Mean 3.98% 4.01% SD 1.01% 0.99%

This first-line supervisor's performance rating for the last five years (X1 to XS) has a mean of 80.2 out of 100 possible (78, 81, 79, 82, 81). For similar type first-line supervisors at your plant, the mean performance rating has been 79.9 (SD 5.01).

This first-line supervisor's last period (X6) performance was 143,600 units of production with a 2.72% sampled defectives. During this period operations were "normal" in terms of the number of days worked, amount of overtime, supply problems, machine breakdowns, etc.

For each of the scales below, mark how much you think each was a cause of this first-line supervisor's last period (X6) performance. You mus t mark each scale.

[] [] [] [] [] [] D [] [] Task No Task ease influence difficulty

[] D [] [] [] D [] [] [] The first-line No The first-line supervisor's influence supervisor's lack of effort extreme effort

[] [] [] [] [] D [] [] [] The first-line No The first-line supervisor's lack influence supervisor's of leadership high leadership ability ability

[] [] [] [] I-I D [] [] [] The first-line No The first-line supervisor's lack influence supervisor's of decision high decision making ability making ability

[] [] [] [] [] [] [] [] [] The first,line No The first-line supervisor's high influence supervisor's low intrinsic motiva- intrinsic tion motivation

[] D [] [] [] D [] [] [] High No Low extrinsic influence extrinsic motivation motivation


[] [] Workers and the first-line supervisor's total lack of cooperation

[] [] Workers' lack of effort

[] [] Workers' lack of ability

[] [] Lack of validity of the production measurement process

[] [] [] [] [] [] No

influence

[] [] ID [] [] [] No

influence

[] [] [] [] [] [] No

influence

[] [] [] [] [] [] No

influence

[] Workers and the first-line supervisor's total cooperation

[] Workers' extreme effort

[] Workers' high ability

[] High degree of validity of the production measurement process

Attributions, cognitive processes and control systems

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