the effect of cognitive style and sponsorship bias on the

The Effect of Cognitive Style and Sponsorship Bias on the

Treatment of Opportunity Costs in Resources Allocation Decisions

H. Alfian

(Fakultas Ekonomi Universitas Lambung Mangkurat, Banjarmasin) Abstract

The current research seeks to identify factors that may potentially influence the way managers respond to opportunity costs when relevant data are not explicitly provided. Identification of such factors should enhance our understanding of why some managers respond to opportunity costs in ways that may be inconsistent with normative economic theory. This information could then be used to identify those situations in which structural and procedural precautions are necessary to correct limitations and biases in human information processing and so ensure the correct treatment of opportunity costs.

Disability of individual processes of perception dimension of Jungs’ typology on research of Chenhall & Morris (1991) to explain difference of managers’ way to making decision, lead us to research questions are: first, which cognitive style combination have a proclivity to incorporate implicit opportunity costs in their economic analysis? Second, used of two dimensions of cognitive style, will project sponsorship encourage managers to ignore negative economic signals derived from opportunity costs that are nevertheless relevant to the resource allocation decision?

A laboratory experiment with 2x4 factorial designs was used to investigating the effect of cognitive style on the managers’ decision of opportunity costs in situation of absence sponsorship or not. The results indicated that intuitive managers tended to incorporate opportunity costs in their decisions whereas sensation individuals appeared to focus more on the directness of the relationship between expenditure and a project to determine the relevance of the cost. Opportunity cost implications tended not to be identified by the sensation group. Evidence was found that sponsorship moderated the influence of cognitive style on decision to include opportunity costs.

1. INTRODUCTION

The incorporation of opportunity costs into resources allocation decisions is

stressed in normative approaches to both management accounting (Horngren & Foster,

1987) and capital budgeting (Brealy & Myers, 1984). However, empirical evidence on the

way managers respond to opportunity costs has revealed a variety of behaviours. Some

studies have demonstrated that managers do include opportunity costs (Neumann &

Friedman, 1978; Friedman & Neumann, 1980), while others have questioned whether

decision makers correctly include the concept in their resources allocation decisions

(Becker et al., 1974; Buzzell & Chussil, 1985; Northcraft & Wolf, 1984; Kaplan, 1986).

Several studies have demonstrated that decision makers tend to include opportunity cost

data only when explicitly provided (Friedman & Neumann, 1980; Northcraft & Neale,

1986). However, research on decision making in organizations indicates that managers

frequently lack knowledge about alternatives (March, 1987). Typically, managers do not

have explicit and relevant information on a well-defined set of alternatives. March (1987)

refers to the identification of alternatives as the main uncertainty facing managers in the

decision making process. Chenhall & Morris (1991) examined how managers treat

opportunity costs in the common decision situation where explicit information on these

costs is lacking. Chenhall & Morris (1991) argued that decision makers’ cognitive style1_,

and the existence of project sponsorship, will influence their response to opportunity

costs in situations in which the relevant information is implicit.

The current research seeks to identify factors which may potentially influence the

way managers respond to opportunity costs when relevant data are not explicitly

provided. Identification of such factors should enhance our understanding of why some

managers respond to opportunity costs in ways that may be inconsistent with normative

economic theory. This information could then be used to identify those situations in

which structural and procedural precautions are necessary to correct limitations and

biases in human information processing and so ensure the correct treatment of

opportunity costs.

The paper argues that decision makers’ cognitive style, and the existence of

project sponsorship, will influence their response to opportunity costs in situations in

which the relevant information is implicit. In particular, the research considers the extent

to disability of individual processes of perception dimension of Jungs’ typology on

research of Chenhall & Morris (1991) to explain difference of managers’ way to making

decision, lead us to research questions are: (1) Which cognitive style combination have a

proclivity to incorporate implicit opportunity costs in their economic analysis? (2) With

combination of two dimensions of cognitive style, will project sponsorship encourage

managers to ignore negative economic signals derived from opportunity costs that are

nevertheless relevant to the resource allocation decision?

The remainder of the paper is structured as follows. First, evidence on the

treatment of explicit and implicit opportunity costs is discussed and theoretical reasons

are advanced as to why opportunity cost signal, which adversely affect a project, may be

ignored. This involves consideration of the effects of cognitive style and sponsorship bias.

2. LITERATURE REVIEW 2.1. Opportunity Cost

Opportunity cost is the forgone benefit that could have been realized from the best

forgone alternative use of a resource (Maher et al., 2006, p.30). Opportunity cost is a

flows of resource allocation decisions. Opportunity cost has been defined as “the cash it

(a resource) could generate for the company if the project was rejected and the resource

sold or put to some other productive use” (Brealy & Myers, 1984, p. 87). Thus,

opportunity costs arise from alternative future uses of existing assets as well as from

alternative uses of future out-of-pocket cash flows.

An important consideration in determining opportunity cost is knowledge of the

next best alternative. Zero opportunity costs implies that the asset is linked specifically to

a project and has no alternative uses including

2.1.1. Explicit Versus Implicit

Research on the treatment of opportunity costs has investigated whether managers

include them in ways consistent with normative economic theory (e.g. Becker et al.,

1974; Neumann & Friedman, 1978; Friedman & Neumann, 1980; Hoskin, 1983;

Northcraft & Neale, 1986). While the evidence on the treatment of opportunity costs is

somewhat mixed, decision makers seem to include them if the opportunity cost data are

provided explicitly. Becker et al. (1974) found that subjects in an experimental situation

made decisions that indicated they either ignored or discounted opportunity cost

information. Neumann & Friedman (1978) modified the experiment by presenting

explicit information about opportunity costs and found that this triggered subjects to use

it. Two studies of Friedman & Neumann (1978 and 1980) found that subjects did use

opportunity cost information when the information was provided explicitly. However, the

subject did not try to impute amounts of potential opportunity costs when no information

was provided regarding their magnitude. The authors concluded that opportunity cost was

included only when it was explicitly available. Further evidence confirming the view that

individuals tend to include explicit opportunity cost is provided in studies by Hoskin

In summary, existing studies have provided support for the view those managers

tend to include opportunity costs when explicit information is provided on alternatives.

However, we have little understanding of why some managers exclude opportunity costs

in the more ambiguous, and common situation, where alternatives are not explicit. The

current study seeks to identify factors which may help explain why some managers do not

treat implicit opportunity costs in ways consistent with normative theory. The research

seeks to provide evidence relating the treatment of implicit opportunity costs to an

individuals’ cognitive style and to whether or not the individual has sponsored the project.

2.2. Cognitive Style

Cognitive style is the concept and the way individual perceive opportunity cost

defined as the way an individual processes, transforms and restructures stimuli received

from the environment to shape a resulting response (Doctor & Hamilton, 1973). The

importance of studying personality and cognitive style in accounting emphasized the need

to understand user characteristics in order to design better information systems (Gul,

1984; Brownell, 1981; Dermer, 1973; Benbasat & Dexter, 1979). Gul (1984, p. 246)

summarized the purpose of studying individual characteristics by stating that research

into the effects of personality seeks to “facilitate the preparation of accounting

information that is most suited to the user’s information processing needs.”

There have been several ways of specifying cognitive style. Doctor & Hamilton

(1973) developed a conceptual scheme which classified individuals as high or low

analytics. High analytics tend to experience the specific aspects of their environment as

discrete from the organized background rather than merged together, while low analytics

have difficulties in perceiving parts of their environment as discrete. Low analytics focus

on the broad situation and these influences the way different aspects are experienced.

which he describes as “analytics” and “heuristics”. The former deals with information in

a structured, rational way building up understanding from clearly identifiable parts. The

latter tends to grasp situations in their totality rather than constructing them from the

separate parts. Evidence suggests that analytics are better suited to task which can be

approached in a structured and repetitive way, while heuristics are better suited to

grasping new situations quickly (Mock et al., 1972; Vasarhelyi, 1977).

While the basic concepts of analytic and heuristic cognitive styles have been

clearly articulated, the means of measuring these styles have varied. Blaylock & Rees

(1984) suggested that a lack of reliable measurement has been responsible for the

disappointing findings of studies which have examined the relationship between cognitive

style and behaviour.

A consequence of these limitations has been the advocacy of the Jungian

typology of cognitive styles and the use of the related and widely validated Myers-Briggs

Type Indicator (MBTI) (Henderson & Nutt, 1980; Blaylock & Rees, 1984). In

summarizing recent research on cognitive style, Blaylock & Rees (1984) suggested that

the Jungian typology provides a particularly useful approach to examine how managers’

cognitive style affects their information preferences and decision behaviour. One aspect

of the Jungian typology distinguishes two modes for “taking in”, or perceiving,

information – “sensation” and “intuition”, this distinction may be linked in a general way

to the analytic and heuristic classification, with the former relating to sensation and the

latter to intuition. The Jungian typology is more descriptive of cognitive characteristics

that affect the way individuals perceive accounting information.

Jungian theory is a multi-dimensional concept that relates to individual processes

of perception (sensation or intuition), attitudes (extroversion or introversion), processes of

(judgement or perception) (Myers & McCaulley, 1985 in Chenhall & Morris, 1991).

Combination dimension of “processes of perception (sensation or intuition)” and

dimension of “processes of judgement (thinking or feeling)” were chosen for the current

study on the basis of the particular theoretical arguments linking it to individuals’

cognitive style.

Taggart & Robey (1981) proposed that an individual’s cognitive style is

determined by pairing of one’s perception and judgement tendencies, combined of two

dimensions of cognitive style Jungian typology will resulting four cognitive styles are as

follows: sensation/thinking (ST), sensation/feeling (SF), intuition/thinking (IT), and

intuition/feeling (IF). Characteristics of each style are presented in table 2.1. (appendix

1).

Further, Taggart & Robey (1981) describe that an individual with an ST style uses

senses for perception and rational thinking for judgement. The ST-style person uses facts

and impersonal analysis and develops greater abilities in technical areas involving facts

and objects. In contrast, a person with an IT style focuses on possibilities rather than facts

and displays abilities in areas involving theoretical or technical development. This style

would enhance the performance of a research scientist. Although an SF person likely is

interested in gathering facts, he or she tends to treat others with personal warmth,

sympathy, and friendliness. Finally, an individual with an IF style tends to exhibit artistic

flair while relying heavily on personal insights rather than objective facts.

A few studies that use the typology to explain decision makers’ broad preferences

for information related to accounting and resource allocation decisions (e.g. Henderson &

Nutt, 1980; Blaylock & Rees, 1984). The way in which cognitive style influences

decision makers’ preference for cost data has not been investigated. However, plausible

opportunity costs may be deduced from the way the characteristics of sensation and

intuitive styles influence individuals’ framing of decision problems.

2.2.1. The Framing of Resources Allocation Decisions

Tversky & Kahneman (1981) proposed that psychological factors influencing the

perception of decision problems produce shifts of preference when different individuals

consider the same problem. They refer to these preferences as “decision frames”, and

claim that the formulation of frames is controlled partly by the personal characteristics of

the decision maker.

In the current research cognitive style is used to explain how individuals, with an

intuitive (IT and IF) cognitive style, frame the decision of cost relevance in ways that

enable implicit opportunity costs to be perceived, whereas sensation (ST and SF)

managers frame the problem in ways that lead to the incorrect treatment of opportunity

costs and consequently wrong decisions.

Consider the cost items which typically are associated with a capital resource

decision and their treatment from the viewpoint of normative economic and accounting

theory (Brealy & Myers, 1984). A variety of future out-of-pocket expenditures will

usually be incurred and will always be relevant. It is the characteristics of specificity of

the link between the asset and the project, and potential alternative uses for the asset that

are important in considering how cognitive style influences the way individuals frame

decisions involving opportunity cost data.

Intuitive (IT and IF) individuals have a broad frame of reference. They focus on

the global situation and are more able to move from specific data to broad abstract

notions. Consequently, we expect intuitive to identify more readily the possibility that

in project evaluation. Their evaluation will be framed from a holistic formulation taking

into account a broader spectrum of potential economic consequences.

Sensation (ST and SF) individuals are concerned with specific and concrete

information. These individuals are less likely than intuitive to perceives alternatives

associated with existing assets unless information on their, use are provided explicitly.

Sensation individuals will tend to treat as irrelevant opportunity cost information,

used by a project, but which do not have specific links to the project. An example would

be spare capacity of machine justified on an earlier project, but available for the current

investment. This decision is likely to be maintained even when the asset has potential

alternative uses, and consequently has positive opportunity costs.

2.3. SPONSORSHIP BIAS

In this study sponsorship bias is identified as one aspect of the social context

which may influence the way in which manager process information related to resource

allocation decisions and that this influence may modify the effect of cognitive style.

The importance of sponsorship bias to the current study is that managers who

include implicit opportunity costs in non-sponsorship situations, may be motivated to

exclude when they sponsor the project. This effect is based on the proposition that once a

commitment to a project has been made, managers are likely to maintain their advocacy

for the project with great stability and tenacity, even when faced with negative signals.

March (1987) commented on the propensity of managers to see things that are consistent

with their viewpoint and noted that responses may include selective perception and

rationalization.

The phenomenon of “escalating commitment” has been suggested as a theoretical

negative feedback on its likely outcome (Duhaime & Schwenk, 1985). Schwenk (1986, p.

304) summarized the notion of escalating commitment:

Many different personal and organizational decisions involve an initial commitment of resources (time, effort, money, etc.) followed by results which suggest initial failure and a need for additional commitment which may save the venture.

Staw & Ross (1978) referred to this phenomenon as “retrospective rationality”,

and argued that further commitment to a failing course of action is an ego-defensive

response which will be particularly pronounced when the individual is personally

responsible for the course of action. Evidence on escalating commitment can be found in

a wide variety of decisions ranging from international politics to business organizations

and individuals (Duhaime & Schwenk, 1985; Staw, 1981).

The basic proposition being asserted is that, the absence of sponsorship bias, the

treatment of implicit opportunity costs in resource allocation decisions will be associated

with an individual cognitive style to take in information. In particular, it is suggested that

in situation with or without sponsorship, managers with sensation/thinking (ST) cognitive

style will tend to include opportunity cost information although it have zero opportunity

costs, whereas those with intuition/thinking (IT) cognitive style will exclude them. The

manner in which cognitive style is expected to influence the treatment of opportunity

costs of decision makers. The effects of cognitive style and sponsorship bias before

interaction presented as the following hypothesis:

H1: Before interaction, in situation with or without sponsorship, managers with sensation/thinking (ST) cognitive style will tend to include opportunity cost information in their resources allocation decisions although it have zero opportunity costs, whereas those with intuition/thinking (IT) cognitive style will exclude them.

There has been no clearly articulated theory as to why social processes, such as

sponsorship bias should dominate over the influence of cognitive style. However, several

commentators have stresses the need to consider the social environment as a potentially

dominating factor which can modify individual attitudes and behaviour (Neisser, 1976

and Pepitone, 1981 in Chenhall Morris, 1991). It is not that cognitive style does not affect

behaviour, rather that there are many other contextual factors which may dominate

behavioural responses.

Libby & Lewis (1982) in Chenhall & Morris (1991) suggested that one of the

difficulties of identifying the influence of psychological factors, such as cognitive style, is

that in any given situation many factors influence how individuals process information.

These additional factors may be either psychological, social, organizational or

environmental. Blaylock & Rees (1984) argued that the diverse results of existing studies

into the effect of cognitive style may be due to a lack of comparability between the

research settings of different studies.

The motivational impact of sponsorship bias on managers to exclude negative

economic signals, form the basis for formulating the interaction hypothesis of this study.

This hypothesis identifies an interaction between the effect of cognitive style and

sponsorship bias. We expect managers who, in non-sponsorship situations, may have a

proclivity to include past expenditures because of their cognitive style, to exclude them

when sponsoring the project. Specifically, sponsorship will cause those intuitive

managers who include general purpose assets, and sensation managers who include

expenditure on specific assets, to reverse their decisions and to exclude the items. The

interaction is ordinal as we expect managers who elect to exclude in non-sponsorship

To summarize, the hypothesis relating sponsorship bias to the current study

proposes that the effect of cognitive style, which generates include decisions, will be

confounded by sponsorship bias.

H2a: Interaction between project sponsorship bias and managers’ cognitive style affecting their treatment of opportunity costs.

H2b: Interaction between project sponsorship bias and managers’ cognitive style affecting managers with intuition/thinking (IT) cognitive style will tend to include opportunity costs information rather than managers with sensation/thinking (ST) cognitive style in resources allocation decisions.

3. METHODOLOGY 3.1. Research Design

A laboratory experiment with 2x4 factorial designs with Friedman & Neumann’s

(1980) multiple time-series research design was employed to investigating the effect of

cognitive style on the managers’ decision of opportunity costs in conditions with and

without sponsorship bias. Myers-Briggs Type Indicator (MBTI) used for determining

subjects’ cognitive style.

Cases and scenario was written that asked each subject to make a series of twelve

sets of decisions between two products having unequal margins. At the outset of the

experiment, each subject was asked to assume the role of a middle-level manager who

must recommend one of two mutually exclusive products. The subjects were told they

would be given some data and that it was economically feasible to request up to two

items of additional information, but that any information in excess of two items was

prohibitively expensive. This scenario was followed by a set of instructions.

After receiving the instructions, subjects were presented information about the

revenues and variable costs associated with each of two products and asked to choose

between the two products (choice 1). Once the choice was made, subjects were given

associated with one of the projects. The magnitude of these amounts was not disclosed.

The subjects were then asked to make the choice again (choice 2). The subjects were then

told that farther information could be obtained in two of five information categories. The

five categories included one outlay cost item, one opportunity cost item, and three items

of fixed costs (allocated, joint costs, or the current interest rate). Since three of the items

were irrelevant, an informed decision maker would be expected to request the outlay and

opportunity cost information. At this point, the subject could choose zero, one, or two

items of additional information. There was no incentive, however, for choosing less than

two items.

The two relevant items of additional information included opportunity costs.

While it is unlikely that decision makers would ignore relevant information, our research

design included a control that permitted us to evaluate whether subjects ignored relevant

information or not. As a test of how subjects used relevant information, the first choice of

each decision set checked that subjects were (margin) maximizers, this test is

manipulation check step 1.

Subjects were not informed that this study concerned use of opportunity costs. As

soon as the subject requested the additional information, it was presented in tabular form

and once again a decision was requested. After the third decision, the entire process was

repeated. Every subject completed twelve different sets of three choices each.

The questionnaire was extensively pre-tested using pilot test with Master of

Science students in Accounting. The pre-testing process resulted in substantial revision of

the program and decision choices. Also, the pretesting process revealed that in most cases

"learning" (i.e., familiarization, maturation, and experimentation) took three decision sets.

Based on these results, researcher decided to consider the first three decision sets part of

Of the nine remaining decision sets, six were experimental and three were control

choices. In the control choices, the correct choice was not sensitive to the additional

information. They were used for three purposes. First, since in the six experimental

choices, the subjects were expected to change their decisions based on the additional

information, the control choices guarded against subjects who might attempt to learn the

experimental strategy and replicate some obvious pattern of responses. Second, one

control choice had only one item of relevant information. Thus, subjects could not always

assume two items of information were appropriate. Third, the control choices enabled us

to determine which subjects were not taking the task seriously, were responding

randomly, or were ignoring some outlay cost information. Any subject who answered

incorrectly on more than one of the control choices was considered to belong to one of

these categories and was therefore excluded from the analysis.

In each of the experimental cases, a correct decision required a switch in choice

of project between the initial decision and the final one. The twelve sets of three decisions

can be categorized into four groups:

Learning Choices : 3 sets (Case 1) Control Choices : 3 sets (Case 2) Experimental Choices : 6 sets (Case 3 & 4)

Consequently, this study starts with no opportunity cost information disclosed (choice 1),

then presents some non-quantitative opportunity cost information for one project in the

pair (choice 2), and concludes with disclosure of the monetary amounts of opportunity

costs associated with each project (choice 3).

3.2. Subjects

The subjects were students of executive programme Master of Management

(MM). The programme was designed for the general manager and this was reflected both

prior experience with capital resource allocation decisions and with sophisticated capital

budgeting techniques, including discounted cash flow analysis. A few were already

general managers, others were being prepared for this responsibility.

4. RESULTS AND DISCUSSION 4.1. Results

A total of 131 of students’ executive programme Master of Management (MM)

are participated in the experiment consist of 84 male and 47 female. The treatment group

of 66 subjects was provided with sponsorship cues. The control group of 65 subjects had

no sponsorship cues. Random assignment of subjects assisted in equating the treatment

and control groups on condition other than sponsorship bias, thereby enhancing the

internal validity of the study. All subjects completed the MBTI cognitive style instrument.

The first phase is the identification of subjects’ personality types using MBTI

questionnaire.

4.1.1. Results of Manipulation Check

Two steps of manipulation check are conducted to decide total samples for

hypotheses testing. In the first step, nine subjects is eliminated since they made the wrong

decision for the first choice for each case more than once-showing that they do not

understand the case and they are not a margin maximizer.

In the second step, another four subjects is eliminated since them as they made the

wrong decision for the second case more than once. Thus, the final samples used for

analysis are 118 subjects. Table 4.1 (appendix 1) present the distribution of the final

samples.

Table 4.2 (appendix 1) reveal the present of unequal of subjects distribution among

with IT and IF cognitive style – even, two cells have less than 5 subjects. The subjects

distribution forbid the performing of further analysis since it is not reasonable to compare

a cell with 40 subjects and another cell only with one subjects. This phenomenon can be

used as a warning by further researchers in determining number of cells or factorial

design used in experiment.

Although, if hypothesis testing is conducted, results show a significant effect of

sponsorship variable and it interacts with cognitive style variable (see table 4.2 and table

4.3 in appendix 1).

4.2. Discussion

4.2.1. Descriptive Statistics

Result indicates that subjects consider explicit information as a dimension of an

important opportunity cost variable. Subjects change their decision as soon as they

receive information describing explicit opportunity cost (choice in Decision 3). This

results apply on 115 out of 118 subjects analyzed, showing that subject hesitant to relate

their decision with opportunity cost when there is no information about the magnitude

(explicitly available) as described by table 4.4 (appendix 2).

Results also show that 101 (85 %) subjects ask for the relevant additional

information, with 79 (66.9%) subjects using the information correctly in decision-making

(table 4.5 - appendix 2).

4.2.2. Additional Analysis

A sample with proportional distribution is used to analyze subjects’ behaviour in

resources allocation decisions. The first step conducted is examining dimension process

of perception of cognitive styles (sensation versus intuition) – as used by Chenhall and

Morris (1991). The total 118 samples consists of 100 subjects’ (84.7%) sensation style

The second step conducted is examining dimension process of judgement of

cognitive styles (thinking versus feeling). The total 118 samples consists of 83 subjects’

(70.3 %) thinking style versus 35 subjects’ (29.5 %) feeling style as shown in table 4.7

(appendix 3).

The third step conducted is examining combination of sensation/thinking (ST)

versus sensation/feeling (SF) which had proportional data structure. The total 100

samples consists of 69 subjects’ (70.3 %) ST cognitive style versus 31 subjects’ (29.5 %)

SF cognitive style as shown in table 4.8 (appendix 3).

The two-way ANOVA test provides results as follows. First, there is a statistically

significant main effect of sponsorship variable—supporting the expectation that manager’

resource allocation decision is influenced by his involvement in a project. Second,

cognitive styles variable do not have a significant main effect in manager’s decision.

Finally, interaction of both sponsorship bias and cognitive styles variables has a

statistically significant effect on managers’ resource allocation decision (F=6.338 and

p-value=0.013), consistent with Chenhall and Morris (1991). It shows that manager’s

involvement in a project and his cognitive styles will influence the decision he made.

5. CONCLUSION, LIMITATION, AND IMPLICATION 5.1. Conclusion

The results of this study provide support for the notion that the treatment of

implicit opportunity costs by managers is influenced by their cognitive style. This study

also provides support for the proposition that the effect of cognitive style may be

confounded by the existence of project sponsorship.

may be significant, but the results will not useful without proportional structure data

support. Additional test beside hypotheses test was done as alternative for making better

result of this study.

That is, without sponsorship, sensation managers dominantly included the

opportunity costs information, a decision which is consistent with the idea that managers

were responding to the specificity of the cost. However, sponsorship confounded this

effect as the managers who felt commitment to the project elected to exclude the items.

The intuitive managers tended to exclude in both situations. This study is consistent with

Chenhall & Morris (1991) and Friedman & Neumann (1980).

5.2. Limitation

This study is limited in the same respects as any laboratory study: First, lack of

overall generality, indeterminant external validity, lack of motivation, and unfamiliar

setting. Second, another limitation was that some undetected mathematical errors may

have been made by the subjects. Some subjects may not have understood the task even

after excluding learning decision sets. This lack of understanding would have the effect of

decreasing the likelihood of correct responses, so that the percentage of decision sets in

which opportunity cost information is used would have been understated. Third,

combination of intuition/thinking (IT) and intuition/feeling (IF) population are scarce,

consequently this study have difficult get the proportional sample size.

5.3. Implication

However, given these limitations, the study does provide some evidence which

helps to explain how managers treat implicit opportunity costs and thereby assists in

addressing the observation by Kaplan (1986) that opportunity costs is often incorrectly

There are two important implications of the study for the design of administrative

systems. One concerns formal systems for the authorization of capital expenditures, and

the other, formal organization structures and responsibilities.

The first implication is that capital budgeting procedures must be designed to

correct the tendency of sensation managers, who constitute 56% of the managerial

population and 62% of financial executives (Myers & McCaulley, 1985 in Chenhall &

Morris, 1991), to mis-specify the treatment of existing assets. This is particularly serious

because academic texts (e.g. Horngren & Foster, 1987), suggest that financial executives

should be responsible for capital budgeting processes and empirical studies confirm this

to be so in the majority of cases (e.g. Gitman & Forrester, 1977 in Chenhall & Morris,

1991). Given that capital budgeting procedures will tend to be designed and administer

managers with a sensing cognitive style likely that mis-specification of the treatment

existing will be embedded into the computer programs and review procedure that

constitute the formal processes. Knowing that the errors are due in part to the

predominant cognitive style of the managers’ response for the design and administration

of the capital budgeting process suggests that the specifying and designing this key

component the resource allocation process should be trusted to a multi-disciplinary team

contains different skills, priorities, and cognitive style

The second implication concerns an appropriate response to sponsorship bias.

The issue complex, on the one hand, capital investment acceptance and ultimate success

appear too enhanced by a manager adopting a role “project champion” (Bower, 1972). On

the other hand, the potential to ignore relevant costs ultimately result in diminished

economics turns, by which time the sponsor could moved on to other responsibilities. It is

post that audits of major projects by an independent organizational unit would indicate

information will only available after the event, any systematic be should become evident

and corrective actions may be taken.

Clearly, managerial decision making on relevance is influenced by many

individual organizational and environmental factors. The current study has examined only

two such factors. Further research in this area should endeavours to uncover the