CONCEPTUAL LEVELS AND THE DESIGN OF ACCOUNTING INFORMATION SYSTEMS

CONCEPTUAL LEVELS AND THE DESIGN OF ACCOUNTING INFORMATION SYSTEMS*

Danny Miller, McGill University Lawrence A. Gordon, McGill University

ABSTRACT

This article attempts to expand and clarify the discussions in the literature on

(a) affecting the cognitive conceptual level of an individual through the financial reporting system can be accomplished not only by varying the immediate information load, but also, in the long run, by modifying the types of information and the mode of usersystem interface. In other words, a properly designed accounting information system can have developmental cognitive effects in both the short and long run. (b) attempting to maximize the conceptual level of the decision maker is not always desirable. In certain types of environments, a high conceptual level actually impedes appropriate decision making. Therefore, the appropriate conceptual level must be related to the type of decision being made as well as to the type of decision maker.

complexity theory applied to accounting via two central assertions:

INTRODUCTION

Information systems and decision making models have become of increased concern to accountants. In fact, the American Accounting Association has sponsored special committee reports on these topics (e.g., [2] [3] ). “The Report of the Commit- tee on Accounting Theory: Construction and Verification” [ I ] concluded that accounting is best viewed as serving the measurement-communication function of the decision making process and that accountants qua metricians have to play an integral part in the decision making process. They point out that

. . . [Accountants] must become involved in the construction, refinement and elaboration of decision models [ 1, p. 611.

The interrelationships between the accounting information system and decision making practices are currently being explored from many perspectives. In this article we shall adopt a psychological perspective in addressing the literature on ‘complexity theory’.

Revsine [22] and Miller [21] have discussed how the complexity of the financial reporting environment might influence decision making behavior through a psychological mediating construct--the conceptual level. These authors raise the possi- bility that as accounting reports increase in complexity beyond a certain point, the

*The authors wish to express their appreciation to Dr. Lawrence Revsine and two anonymous referees for their comments on earlier drafts of this paper.

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260 DECISION SCIENCES [Vol. 6

user’s ability to make judgments on the basis of this information conceivably could diminish. This article attempts to expand and clarify the discussions in the literature on complexity theory applied to accounting via two central assertions:

(a) affecting the conceptual level through the financial reporting system can be accomplished not only by varying the immediate information load, but also, in the long run, by modifying the types of information and the mode of usersystem interface. (b) attempting to maximize the conceptual level of the decision maker is not always desirable. In certain types of environments, a high conceptual level actually impedes appropriate decision making.

We shall briefly discuss the nature, determinants and behavioral repercussions of the conceptual level. The empirical evidence cited will help provide subsequent researchers with information on some key behavioral variables which may be used in arriving at a contingency theory for the design of accounting information systems.

FACTORS AFFECTING CONCEPTUAL LEVEL

Conceptual level, also known as the level of cognitive complexity, refers to two basic features of the cognitive system: the number of dimensions taken into account in formulating a judgment (Lea, the degree of differentiation) and the nature of the rules used to combine these dimensions in arriving at a f i a l decision (i.e., the level of integration). For example, an individual with a high or ‘abstract’conceptud level will, in deciding whether to market a new product, consider a large number of variables such as costs, competitive reactions, market potential, economic conditions, etc. In ‘combining’ these dimensions to make his decision he will be capable of perceiving alternate perspectives of the situation. He may have an array of rules which are tailored to the specific circumstances at hand and which can change according to basic trends in the environment. In contrast, those who possess low or ‘concrete’ conceptual levels will focus on only a few variables in a decision situation and will tend to combine these to form a judgment using fixed and singular rules [ 13, pp. 24-26 and

Schroder, Driver and Streufert [25, pp. 45-66] have gathered evidence which indicates that the conceptual level is a function of two broad classes of factors. The first represents the effects of long-term training conditions under which a ‘concept’ is formed and is termed dispositional. The second class arises out of the characteristics of the immediate environment and is called conditional.

Revsine [22] and Miller [21] have treated conditional factors in their respective articles. Based upon the findings of Schroder, et al. [25] , they suggest that environmental complexity induced by expanding the range of data provided in financial reports can influence the level of cognitive complexity (conceptual level) brought to bear on a decision. Stated differently, they argued that the information load, as determined by data expansion or contraction, can move an individual along a given curve. This relation is illustrated in Figure 1.’

76-77] [26, pp. 242-2541.

‘Revsine’s article (including footnotes) provides an excellent exposition on conditional factors.

19751

HIGH

Conceptual Level

LOW

ACCOUNTING INFORMATION SYSTEMS

FIGURE 1

26 I

LOW HIGH Environmental Complexity

Figure 2 shows a sef of curves which describe another dimension of the relationship between environmental and conceptual complexity. Schroder, Driver and Streufert [25, pp. 46-53], and Harvey, Hunt and Schroder [13, pp. 113-1571 have hypothesized that the level of these curves for a given individual or group is determined by the long run training characteristics of the environment.

FIGURE 2

HIGH

Conceptual Level

LOW

Interdependent

Autonomous (b) Unilateral (a)

LOW HIGH Environmental Complexity


The conceptual level brought to bear on a decision making task will thus be an interactive function of both the complexity of the immediate environment which will determine the point along a given curve of Figure 2 and the dispositional factors or training conditions which determine the level of the curve. Long term training conditions, which may be influenced by the accounting information system, can shift the individual from one dispositional curve to another (e.g., from A to B in Figure 2).293

The key long-run training variables which influence conceptual level are the diversity (complexity) and conflict induced over extended periods in the learning situation [13, Chapter 51 [ 2 5 , pp. 45-53]! According to Schroder, Driver and Streufert [ 2 5 , p. 461 :

. . . conditions that are either oversimple or overcomplex lead to the arrest of development at some point along the concrete-abstract dimension . . .. Condi- tions that produce too much diversity (complexity) will eventually retard the development of effective schemata for integration, and result in a more concrete structure. Conversely, conditions that fail to induce enough diversity, conflict, or complexity, retard the development of abstract system properties.

Thus, the type and quantity of data provided by the accounting information system and the proclivity of that data to elicit conflicting perspectives of a situation could entail significant training variables. This result of course is contingent upon whether managers actually use such data in decision making.

For example, if the accounting information system portrays only a few financial variables, it entails a fairly simple and not very diverse aspect of the training environment of the decision maker. If, on the other hand, voluminous reports are supplied and the array of factors portrayed conjures up different interpretations of what has taken place (or might occur in the future), the training environment could be con- sidered complex.

We shall proceed to examine the influence of three types of training environments, each implying a different level of complexity, on the dispositional level of cognitive complexity of the manager. We shall also consider the types of accounting information systems which might be indicative of each of these types of training conditions.

’Miller [ 2 l ] pointed out that different individuals (or groups of individuals) may be on different curves. Shifting an individual or group to a different curve was not mentioned as a potential repercussion of the information system characteristics.

3Complexity theorists hypothesize that individuals with abstract conceptual structures are expect- ed to reach the highest point along their conceptual curve in more complex environments, while concrete individuals reach their maximum at lower levels of environmental complexity (Miller, [ 2 1 ] ). D. Wilson’s [42] note indicates that the issue is in question. Our arguments are not affected by this controversy.

4Robert R. Sterling [31, p. 1061 notes the distinction between short and long-term influences of accounting information on decision making. He points out that “communications are not neutral; instead they are educational. [The accountant] cannot be neutral because his transmissions will be a major factor in determining what the future generations consider relevant.”

19751 ACCOUNTING INFORMATION SYSTEMS 263

Unilateral training conditions prevail when the training agent takes care of all activities involving the structuring and simplification of the trainee’s environment. Everything is spelled out by the trainer. The trainee has only to digest what has been presented. Such training according to Schroder, Driver and Streufert [25] inhibits the trainee from adopting a variety of perspectives and dimensions of the environment. Conceptual structure thus becomes arrested at a low level.

Certain aspects of an accounting information system may influence the extent to which the manager’s decision making environment is ~n i l a t e ra l .~ For example, if reports provide only one static perspective of the firm or one of its sub-segments, the manager will not be exposed to new dimensions or alternative perspectives for viewing a situation. His enLironment will have been structured by the information system in a manner such that no conflict can arise from the perception of alternative perspectives of looking at an issue. If the system presents only historical cost information, it will not serve to point out marketing or behavioral considerations which may add a new, though perhaps conflicting, perspective regarding a problem.

If the accounting information system presents too broad and unstructured an 6 array of information, it provokes what are known as autonomous training conditions.

Here, the system affords so many different ways of looking at the decision problem that the manager is forced to ‘put the blinkers on’ in order to effect timely closure [e.g., 61. Looking at a problem from the marketing, financial, production, economic, competitive and behavioral points of view may be too time consuming and confusing to allow highest levels of conceptual complexity to emerge [25].

Interdependent training settings result in the highest level of conceptual complexity [4]. The diversity and conflict inherent in the accounting information presented will be sufficient to encourage the manager to consider a good number of dimensions and perspectives in regarding a situation. It will not, however, be so high as to provoke a sharply bounded search.

Thus, the various training conditions, through their diversity and induced conflict, imply different modes of user-system interface. Unilateral systems oversimplify the environment and act as a restriction to the emergent conceptual level. Autono- mous systems do not provide sufficient guidance. Only interdependent systems supply an appropriate amount of direction for the emergence of a maximum level of conceptual complexity.

It is important to note that an individual’s conceptual level is a function of many variables within and external to the organization which have nothing to do with the accounting information system. The amount of delegation of authority for decision

’While the accounting information system is only one source of data for a manager, it may be quite an important one. Furthermore, other persons who communicate personally with the manager and influence his thinking may also be affected by a part of the accounting information system. Thus, the combined impact of such direct and indirect influence is likely to be substantial.

%t should be noted that different training conditions may impose the same amount o f information foad upon the individual. The modes differ mainly in the manner in which they provide information diversity and conflict.


making, the extent to which participative management techniques are used, and the variety of functions for which a manager is responsible will all tend to influence the level of dispositional conceptual complexity. Thus, it is too much to hope that the accounting system alone will have a very large impact on dispositional complexity. We can only expect conceptual levels to be substantially affected by a rather broad mix of training factors.

We may consider another feature which can influence dispositional conceptual complexity-the rate of change in the manager’s environment. If we change the environment very rapidly, perhaps by introducing additional diversity, uncertainty and responsibility to the manager’s job and by providing him with increased differentiated or extensive accounting information, we should expect regression in the level of conceptual complexity. Such a result occurs because drastic changes in the task environment act very much like autonomous training conditions. They provide excessive environmental complexity for high conceptual levels. Thus, the features of the task environment can be changed only gradually, will have to extend beyond the realm of the accounting system for optimal effect, and will take time to have appreciable impact.

To conclude, it has been proposed that the accounting information system will influence the decision maker’s situational or conditional complexity (the point on the curve-Figure 1) via the immediate information characteristics supplied at a given instant. The accounting information system can also, over the long run and in conjunc- tion with other task factors, influence the manager’s training environment and thus affect his dispositional conceptual level (level of the curve-Figure 2). Naturally, the extent to which data expansion or diversification immediately lowers or raises conceptual levels will be partly determined by the nature of the existing dispositional curve.

CONCEPTUAL LEVEL AND DECISION MAKING

Let us examine the utility of influencing an individual’s conceptual level. We shall examine this question by looking at some of the repercussions of the conceptual level upon decision making behavior. Many studies [ 141 [36] [26, pp. 263-2671 have compared the problem solving and decision making behavior of high and low complexity individuals in simulated war, community development, political, and business games. While it is important to acknowledge the limitations of such a laboratory approach, the experimental findings are rather compelling in their consistency.

Karlins [ 151 found that high conceptual level subjects exhibited more breadth in information search, searched more evenly across and within information domains, and differentiated more with respect to the importance of various classes of information

19751 ACCOUNTING INFORMA TION SYSTEMS 265

than did low conceptual subjects.’ Karlins and Lamm [ 161, and Suedfeld and Streufert [38] came up with similar findings. In an organizational context, we would expect that problem identification, development, and selection phases would be char- acterized by deep diagnosis, the generation of a great number of alternatives, and thorough evaluation and design by high conceptual managers.

High conceptual level subjects not only search differently for information, they use it differently. This fact is reflected in their approaches to problems and the nature of their decisions8 For example, as a task situation becomes mastered, complex decision makers gain the confidence to take a more active role in structuring it. In contrast, simple subjects less often make decisions that initiate complex or original action. Their ‘solhtions’ amount to nothing more than direct responses to simple stimuli in the environment [ 141 .

However, we must not conclude that simple (low conceptual level) individuals are poorer decision makers or problem solvers than complex persons. Success at solving problems depends upon an isomorphism between conceptual level and the complexity of the problem. Suedfeld and Hagen [37] discovered that simple subjects were better able to solve problems which necessitated the use of only relatively few cues. They were much less effective than complex (high conceptual level) solvers when the use of many cues was required. The total number of problems solved by complex and simple groups was the same, but the nature of the problems differed significantly. Problems which are complex and ill defined are solved more readily by complex individuals, whereas simple, structured problems are more amenable to rapid solution by simple subjects who do not waste their time on peripheral cues.

Perhaps the different approaches to policy-making and decision making can to some extent be explained by differences in the levels of cognitive complexity. Dror [9] outlines a systematic and thorough modus operandi for making policy. It is one which flows logically, considers a broad array of values, expectancies, and alternative courses of action, attempts to take into account complex interaction effects, and strives as far as possible to maximize outcomes. Lindblom [ 181 , and Cyert and March [7], propose that reality is far too complex to treat using such models. They claim

71t should be noted, however, that low conceptual level subjects seem to prefer more information than their high conceptual counterparts 1251. Another author, J. Dermer [Sl, has come to the same conclusion. The f i s t authors attribute the finding to the fact that low conceptual subjects are insensitive to detrimental increases in information load. Dermer claims the finding is due to the fact that low conceptual subjects have a lower tolerance for ambiguity. Either way, these findings have to be qualified with the fact that the amount of information search does not necessarily bear any relationship to the number of relevant facts actually taken into account in making decisions. Dermer’s other findings will not be mentioned here as he has not measured conceptual complexity as prescribed by Schroder and his colleagues. Rather, he concentrates on tolerance for ambiguity- an intuitively related but different variable.

8E. Lusk 1191 showed how one element of cognitive style, field dependedness, influenced the financial decisions of his subjects. Field independent subjects tended to show a preference for investments portrayed by thorough, analytical financial reports. Field dependent subjects preferred investments portrayed by simpler, more aggregate financial statements.


that decision makers cannot take too many variables into account because their cognitive abilities are limited and that successive limited comparisons are used to choose from alternatives. Analysis is drastically bounded. Dror's type of decision-making may be representative of that used by conceptually complex persons, while Cyert and March, and Lindblom, seem to be describing less complex decision makers. What is of interest is that there still exists much disagreement upon which method is most effective. Some policy theorists now feel that the efficacy of the method depends upon the type of situation in which it is used.'

We therefore believe that the conceptual level that is optimum for appropriate decision making and problem solvin will be a function of the type of environment and task which faces the manager." If a firm operates in a stable and unchanging environment and/or the manager is dealing mainly with recurring and straightforward decisions, the accounting information system should be used to limit the evolving conceptual level (through immediate information load or long run training conditions). On the other hand, if a manager's task is complex because he must handle complex problems in a dynamic environment, a high conceptual level might be most appropriate. Again the accounting information system could come into play by influencing information load and diversity.

CONCLUSION

The accounting information system can affect the individual's decision making

1. 2.

behavior through its effects on his conceptual level in two ways: by influencing immediate environmental complexity, and by affecting the long term training conditions which may shift an individual from one dispositional conceptual level t o another.

Thus, the design of the accounting system may be very influential in determining how decision makers respond to given situations. A properly designed system can have effects which are beneficial in both the short and long run.

One could argue that poorly designed accounting information systems have been major hindrances to effective management decision making. For example, most accounting systems only provide managers with absorption costing data. Perhaps as a result, many managers have been trained to think in terms of total average costs, rather than marginal costs (or their crude approximation, variable costs), in decision making. In fact, one of the authors has recently spent time explaining to a company executive why the company's decision rule of eliminating all products whose contribution mar- gin does not cover their share of fixed costs should be reexamined. Unfortunately, the matter is complicated by the fact that a system which is appropriate for one situation may not be appropriate for another. This fact makes the task of designing a single, ideal system, even within a given company, extremely difficult. Yet, an attempt to

'For a further discussion of this point see D. Miller 1201.

"Revsine, in his book (231, also comes to this conclusion (see footnote 27, p. 17).


discover an accounting system which presents the optimal quantity and diversity of information should be made so as to aid the decision maker in attaining a conceptual level that would be appropriate to the type of decision making task he must normally face.

Note that the appropriate conceptual level is a function of decision-making requirements and the nature of the problem at hand. It is not always best to reach the highest conceptual levels. Therefore, any empirical research aimed at determining whether to increase or decrease the environmental complexity, and thereby affect the conceptual level of an individual via the accounting information system (e.g., via data expansion or contraction), must necessarily be related to specific task requirements.

REFERENCES

American Accounting Association, “Report of the Committee on Accounting Theory: Con- struction and Verification,” The Accounting Review, Supplement, (1971), pp. 51-79.

American Accounting Association, “Report of the Committee on Information Systems,” The Accounting Review, Supplement, (1971), pp. 288-350.

American Accounting Association, “Report of the Committee on Managerial Decision Mod- els,” The Accounting Review, Supplement, (1969), pp. 43-76.

Anderson, 0. and 0. Moore, “Autotelic Folk Models,” Sociological Quarterly, (1960), 1,

Bieri, J., “Cognitive Structures in Personality,’’ in H. Schroder and P. Suedfeld (Eds.), Per- sonality Theory and Information Processing, New York: Ronald, 1971.

Braybrooke, D. and C . Lindblom, A Strategv of Decision, New York: Free Press, 1963.

Cyert, R. and J. March, A Behavioral Theory of the Firm, Englewood Cliffs, N.J.: Prentice- Hall, 1963.

Dermer, Jerry, “Cognitive Characteristics and the Perceived Importance of Information,” The Accounting Review, (July, 1973), pp. 511-519. Dror, Y.,PuMic Pdicy-making Re-examined, San Francisco: Chandler, 1968. Gardner, G. and H. Schroder, “Reliability and Validity of the Paragraph Completion Test,” Psychdogv Reports, 1972, pp. 959-962. Harvey, O.,Motivation and Social Interaction, New York: Ronald, 1963.

Harvey, O., and H. Schroder, “Cognitive Aspects of Self and Motivation,” in 0. Harvey (Ed.), Motivation and Social Interaction, New York: Ronald, 1963. Harvey, O., D. Hunt and H. Schroder, Conceptual Systems and Personality Organization, New York: Wiley, 1961. Heslin, R. and S. Streufert, “Task Familiarity and Reliance Upon the Environment in Decision Making,”Psychdogical Record, (1968), 18, pp. 629637. Karlins, M., “Conceptual Complexity and Remote Associative Proficiency as Creativity Variables in a Complex Problem Solving Task,” Journal of Personality and Social Psycho-

Karlins, M. and H. Lamm, “Information Search as a Function of Conceptual Structure,” Journal of Personality and Social Psychdogv, (1967), 5 , pp. 456459.

pp. 203-216.

Ion, (1967), 6, pp. 264-278.

26 8 DECISION SCIENCES [Vol. 6

[17] Karlins, M., R. Lee and H. Schroder, “Creativity and Information Search in a Problem Solving Context,” Psychonomic Science, 1967,8, pp. 165-166.

[ 18) Lindblom, C., ‘The Science of Muddling Through,”PuMic Administration Review, (Spring,

[ 191 Lusk, Edward, “Cognitive Aspects of Annual Reports: Field Independence/Dependence,” paper presented at Empirical Research in Accounting Seminar at the University of Chicago, Spring, 1973.

[20] Miller, D., ‘Towards a Contingency Theory of Strategy Formulation,” working paper, McGill University, 1974.

[21] Miller, Henry, “Environmental Complexity and Financial Reports,” The Accounting Re- view, (January, 1972), pp. 31-37.

[ 221 Revsine, Lawrence, “Data Expansion and Conceptual Structure,” The Accounting Review, (October, 1970), pp. 704-7 11.

[ 231 Revsine, Lawrence, Replacement Cost Accounting, Englewood Cliffs, N.J.: Prentice-Hall, 1973.

[ 241 Schroder, H. and 0. Harvey, “Conceptual Organization and Group Structure,” in 0. Harvey (Ed.),Motivation and Social Interaction, New York: Ronald, 1963.

I251 Schroder, H., M. Driver and S. Streufert, Human Information Processing, New York: Holt, Rinehart and Winston, 1967.

I261 Schroder, H. and P. Suedfeld, Personality Theory and Information Processing, New York: Ronald, 1971.

[27] Scott, W., “Cognitive Complexity and Cognitive Flexibility,” Sociometly, 1962, 25, pp. 405414.

(281 Scott, W., “Conceptualizing and Measuring Structural Properties of Cognition,” in 0. Harvey (Ed.), Motivation and Social Interaction, New York: Ronald, 1963.

[29] Signell, K., “Cognitive Complexity in Person Perception and in Nation Perception,” Journal o f Personality and Social Psychdogy, 1966,34, pp. 517-537.

[ 30) Stager, D., “Conceptual Level as a Composition Variable in Small Group Decision Making,” Journal OfPersQnality andsocial Psychdogy, 1967,5, pp. 152-161.

[ 31 1 Sterling, Robert, “A Statement of Basic Accounting Theory: A Review Article,” Journal of Accounting Research, (Spring, 1967), pp. 95-112.

[ 321 Streufert, S., “Complexity and Complex Decision Making,” Journal of Experimental Social

[33] Streufert, S. and M. Driver, “Impression Formation as a Measure of the Complexity of Conceptual Structure,” Educational and Psychdogical Measurement, 1967, 27, pp.

[ 341 Streufert, S. and H. Schroder, “Conceptual Structure, Environmental Complexity, and Task Perforrnance,”Joumal of Experimental Research in Personality, 1965, 1, pp. 132-137.

[ 351 Streufert, S. and S. C. Streufert, “Effects of Conceptual Structure, Failure and Success on Attribution of Causality,” Journal of Personality and Social Psychdogy, 1969, 11, pp.

(361 Streufert, S., P. Suedfeld and M. Driver, “Conceptual Structure, Information Search, and Information Utilization,” Journal of Personality and Social Psychology, (1965), 2, pp.

[ 371 Suedfeld, P. and R. Hagen, “Measurement of Information Complexity,” Journal of Personul- ity and Social Psychdogy, (1966), 4, pp. 233-236.

1959), pp. 79-88.

Psychdogy, 1970,6, pp. 494-509.

1025-1039.

138-147.

736-740.


(381 Suedfeld, P. and S. Streufert, “Information Search as a Function of Conceptual and Envi- ronmental Complexity,”Psychonomic Science, (1966), 4, pp. 351-353.

[ 391 Tuckman, B., “Integrative Complexity: Its Measurement and Relation to Creativity,”Edu- cational and Psychdogical Measurement, 1966,26, pp. 369-382.

[40] Tuckman, B., “Personality Structure, Group Composition, and Group Functioning,” Sucio- metty, 1964,21, pp. 469481.

[41] Vannoy, J., “Generality of Cognitive Complexity-Simplicity as a Personality Construct,” Journal OfPersonality and Social Psychdogv, 1965,2, pp. 385-396.

1421 Wilson, D., “A Note on Environmental Complexity and Financial Reports,” The Accounting Review, (July, 1973), pp. 586-588.

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CONCEPTUAL LEVELS AND THE DESIGN OF ACCOUNTING INFORMATION SYSTEMS