POSTER TITLE DEVIATIONS FROM RATIONAL DECISION-MAKING: AN INTERACTIVE APPROACH ABSTRACT Whereas the main effects of individual, structural, and environmental factors have been thoroughly examined in the decision-making literature, the paucity of research examining interactions across levels is stunning. In this manuscript, we present an introductory interaction model that lays the foundation for more complex decision-making models.

PRESS PARAGRAPH The present paper posits interactive effects of factors that influence the decision-making process. Whereas the main effects of individual, structural, and environmental factors have been thoroughly examined in the literature, the paucity of research examining interactions across levels is stunning, especially as most decisions are made embedded in complex contexts. In this manuscript, we present an introductory interaction model that lays the foundation for more complex decision-making models.

In recent years, the role of risk in organizations has gained increased recognition as the

consequences of irrational decisions have become more visible. Most scholars who have studied

decision-making behavior regarding uncertain organizational situations have focused on single

determinants of this behavior (Sitkin & Pablo, 1992). Main effects, such as environmental (e.g.,

Astely & Vande Ven, 1983; Griffin, Tesluk, & Jacobs, 1995; Romanelli & Tushman, 1988;

Staw, Sandelands, & Dutton 1981; Venkatraman & Prescott, 1990; Wiersema & Bantel, 1993)

individual (e.g., Driver, Brousseau, & Hunsaker, 1990; Rowe & Mason, 1987; Whyte, Saks, &

Hook, 1997), and structural factors (e.g., Fredrickson, 1986; March & Simon, 1958; Simon,

1976) on these outcomes have been examined and accepted in research. However, this approach

does not reflect the complexity of real life, as decisions are not made in a vacuum where only the

environment or structure or personality of the decision maker(s) influences the decision. This has

led to potentially inaccurate conclusions about the causes of irrational behavior (Sitkin & Pablo,

1992).

The focus of this paper is on the factors that increase the likelihood of deviating from the

rational decision model. More specifically, we suggest that individual, structural, and

environmental factors are all intertwined and thus interact to produce irrational behavior. The

importance of interactions among constructs is threefold. First, instead of believing that one

factor is more important than other factors, we suggest that a new dynamic surfaces as a result of

the interaction. Second, the effects of interactions are not all additive or linear (i.e., some

interactions may result in multiplicative or exponential effects). Finally, to truly understand what

factors lead to irrational decisions and for organizations to be able to more accurately influence

decisions, it is essential to conceptualize an interactive framework.

It is stressed that the importance of this model is the integration across levels. Prior

researchers have suffered from a fragmented, issue-oriented focus that has resulted in overly

simplified models in which a variety of individual and organizational characteristics are posited

to separately influence individual decision making behaviors (Sitkin & Pablo, 1992). We

endeavor to integrate different factors across various levels logically and systematically to

increase knowledge of the interaction of decision-making factors.

LITERATURE REVIEW AND THEORETICAL BACKGROUND As shown in Table 1, there are many factors that influence decision making. It is beyond

the scope of this manuscript to describe and predict how each of these factors interact to impact

decision-making. Instead, in an effort to both highlight the importance of interactions across

levels and provide initial theoretical guidance on how outcomes will be impacted by these

interactions, we present a simplified model that considers only one dimension from each

category (i.e., core self-evaluations, individuals vs. teams, and threat).

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Insert Table 1 about here

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For the purposes of this manuscript, irrational decisions are those that deviate from the

rational decision making model. It is important to note that within this context, irrational

decisions do not comprise those behaviors that are considered counterproductive work behaviors

such as workplace violence and aggression, antisocial behaviors, and paranoia. They do,

however, include those decisions that do not follow basic economic tenants, including risk-

seeking behaviors and non-risk seeking behaviors. As such, each of these behaviors does not

follow basic economic theory and, thus, are considered irrational. Risk-seeking and non risk-

seeking behaviors are further elaborated in the following paragraphs.

Risk-seeking behaviors

According to Sitkin and Pablo (1992, p. 10), risk is a characteristic of decisions that is

uncertainty about whether potentiality significant and/or disappointing outcomes of decisions

will be realized. This definition encapsulates three fundamental elements that are necessary for

its comprehension: outcome uncertainty, outcome expectations, and outcome potential. Risk

behavior can be characterized by the degree of risk associated with the decisions being made. A

decision is riskier to the extent that: (1) their expected outcomes are more uncertain; (2) decision

goals are more difficult to achieve; or, (3) the potential outcome set includes some extreme

consequences (Sitkin & Pablo, 1992).

Non risk-seeking behaviors

Even though the general consensus is that decision makers are non risk-seeking, taken to

the extreme these behaviors can have many damaging effects. It has been well established in

financial theory that the more risky assets must compensate risk-averse investors with higher

expected returns (Huang & Litzenberger, 1988). The more non risk-seeking investors are, the

lower their expected returns on investments will be (Jianakoplos & Bernasek, 1998). Many

times, this applies to agents because they are thought to be more risk-averse while their principal

is more risk-neutral to risk-seeking (Eisenhardt, 1989). Here, non risk-seeking, by itself, is not

enough to be considered irrational; the behavior demonstrated by the decision maker as to be in

excess. Put another way, decision makers avoid potential decisions that have even the most

minute amounts of risk, i.e., they will always go for the sure bet.

Individual differences

While decision making has been the subject of long-standing conceptual concern, despite

some conceptual work (Driver, Brousseau, & Hunsaker, 1990; Rowe & Mason, 1987), there has

been little consideration of the impact of individual differences between decision makers

approaches to or styles of decision making (Spicer & Sadler-Smith, 2005). Thus, different

interpretations of the same problem can be attributed to individual differences in processing

capacity combined with factors such as personality and perception.

Among the most pivotal, fundamental factors of individuals is the rudimentary conviction

they have of themselves. Researchers have long been interested in how a decision makers self-

concept affects his or her behaviors, but have lacked a theoretically grounded, validated

construct for conducting systematic inquiry (Hiller & Hambrick, 2005). However, recent

research has suggested tha t the concept of core self-evaluation (CSE) may concisely summarize

this general self-concept (Judge, Erez, Locke, & Thoresen, 2002; Judge, Erez, Bono, &

Thoresen, 2002; Judge, Erez, & Bono, 1998). Core self-evaluations are the fundamental,

subconscious conclusions individuals reach about themselves, other people, and the world

(Judge, Locke, & Durham, 1997).

Core-self evaluations (CSE) impact an individuals perception of the self. At a basic

level, the high-CSE individual is characterized by self-confidence, self-worth, self-potency, and

freedom from anxiety (Hiller & Hambrick, 2005). Decision makers who are high-CSE

individuals would exhibit more confidence in their decisions due to their high self-confidence

and low anxiety levels. This suggests that these individuals are more likely to display

overconfidence in estimating their certainty when being correct or producing a certain outcome

(Hiller & Hambrick, 2005).

The importance of core-self evaluations, as a personal disposition in decision making, is

how it effects an individuals perception of the self. At a basic level, the high-CSE individual is

characterized by self-confidence, self-worth, self-potency, and freedom from anxiety (Hiller &

Hambrick, 2005). It then makes sense that decision makers who are high-CSE individuals would

exhibit more confidence in their decisions due to their high self-confidence and low anxiety

levels. Taking this another step, these individuals are more likely to display overconfidence in

estimating their certainty when being correct or producing a certain outcome (Hiller &

Hambrick, 2005).

In addition, because CSE has a historical component, i.e., it is reinforced (or diminished)

by long-term feedback processes, and finally, subject to further adjustments in the face of recent

life events (Weinberger, 1994). Therefore, an individual who has had success in the past is more

likely to exhibit a higher CSE than those individuals who have not; thus,

Proposition 1: Decision makers who are high-CSE will be more likely to demonstrate

risk-seeking characteristics than low-CSE decision makers.

Structure

The relationship between organizational structure and decision making behavior has been

a frequent topic for speculation among organizational scientists (Blankenship & Miles, 1968;

Wally & Baum, 1994). However, to understand why it is logical for the decision process to be

affected by structure, one must understand the relationship between decision making and

structure (Fredrickson, 1986). March and Simon (1958) argued that an organizations structure

imposes boundaries of rationality that accommodate members cognitive limitations. By

delimiting responsibilities and communication channels, structure allows organizations to

achieve organizationally rational outcomes in spite of their members cognitive limitations

(Simon, 1976). They suggest that structure helps management to control the decision-making

environment and facilitate the processing of information.

Within the context of this paper, we focus on the differential impact of making decisions

in groups versus individuals. A number of researchers have noted the importance of groups in

decision-making processes (Cohen & Bailey, 1997; Parks & Cowlin, 1995), although most of the

research on decision-making has occurred at the individual level (Moon et al., 2003). It is

therefore important to investigate whether groups and individuals differ on irrational behavior.

Research on group decision making has demonstrated that compared to individuals,

groups sometimes make better decisions (Libby, Trotman, & Zimmer, 1987; Sniezek & Henry,

1989) and sometimes make inferior decisions (Gigone & Hastie, 1997). Thus, neither individuals

nor groups are impervious to irrational decisions.

The concepts of groupthink (Janis, 1982) and group polarization (Whyte, 1989) suggest

reasons why groups may make excessively rash decisions. Groupthink refers to a mode of

thinking that people engage in when they are deeply involved in a cohesive in-group, when the

members striving for unanimity overrides their motivation to realistically appraise alternative

course of action (Janis, 1982, p. 9), whereas group polarization is the tendency for group

discussion to enhance the point of view initially dominant within the group (Myers & Lamm,

1976; Whyte, 1989).

Core self-evaluations and groups

Within groups, CSEs should have a dramatic impact on the decision making process.

Individuals who have high CSEs would have the propensity to engage in both risk-seeking and

escalation of commitment behaviors. Compared to high CSE individuals, high CSE groups are

expected to make even riskier decisions than individuals and commit more resources to failing

endeavors than will individuals. The notion of groupthink suggests that groups have a tendency

to make decisions that are in the extremes, both positively and negatively. Consequently, when

groups with a high overall CSE engage in the decision-making process, initial preferences for

risk will be amplified by groupthink. Because one of the symptoms of groupthink is an illusion

of invulnerability, the overconfidence that is already present by high levels of CSEs will be

intensified by the illusion of invulnerability created by groupthink.

Conversely, groups with low CSEs will be more risk averse than individuals with low

CSEs. When a group has low CSEs, they will lack confidence in their decisions and have high

levels of anxiety. Because the groups initial response to a decision-making situation will be one

that is risk averse, group polarization will exaggerate the risk aversion of the group, producing

decisions that are more risk averse than if an individual alone with the same level of CSE would

make.

Proposition 2: Core self-evaluations and decision structure will interact, such that high-

CSE groups will make the most risky decisions, high-CSE and low-CSE individual will

make moderate risk decisions, and low CSE groups will make low risk decisions

Environment

A popular belief in the business literature is that the competitive environment is growing

increasingly complex, uncertain, and adverse (Harrington, Lemak, & Kendall, 2002). Hitt,

Ireland, and Hoskisson (1999) suggested that organizations in the new competitive landscape

need to have the ability to adapt to environmental change with innovation and speed.

Contingency theorists have asserted that organizations in uncertain environments should create

flexible processes to react effectively to adversity or unanticipated change (Burns & Stalker,

1961; Galbraith, 1977; Lawrence & Lorsch, 1967).

This literature suggests that in order for decision makers to be successful, they need to be

vigilant in their assessment of environmental conditions. However, conditions of threat (i.e., an

impending event that can create negative consequences) impact decision makers ability to reach

rational and effective responses (Staw et al., 1981). According to the threat-rigidity thesis (Staw

et al., 1981), the dominant responses will be maladaptive if the task or environment has radically

changed and adaptive if the causal relationship between process and performance is stable.

Broadly, they suggested that an event that has potentially negative or harmful consequences for

the vital interests of an individual or group leads to a set of responses that tend to be less varied

or more rigid (Griffin et al., 1995).

According to Staw et al. (1981) threats have cognitive and motivational effects on

decision makers. Restriction in information processing may result when stress and anxiety

induced by threats cause decision makers to confine their range of attention and decrease their

awareness of peripheral cues. This makes processing of new or complex information difficult

and restricts alternatives considered to those that are consistent with conservative and well-

learned interpretive frames. Consequently, when under highly threatening situations, individuals

will reduce their effort to search for information (Staw et al., 1981), leading to a sub-optimal

decision.

Core self-evaluations, individuals vs. groups, and threat

We suggest that high CSE groups who face environments that are exceedingly

threatening will make the most risky decisions. Because high CSE groups already have a

predisposition towards risky and escalating behaviors, amalgamating this with a threatening

environment will only exacerbate risk-seeking and escalating behaviors. Due to a predilection for

risk-seeking and escalating behaviors, group polarization will be exacerbated by the threat that

the group experiences. However, threat will only exacerbate the level of risk-seeking and

escalating behaviors if the group makes internal attributions for the threat (Harrington et al.,

2002).

The least risky behaviors would be expected from low-CSE groups experiencing high

levels of threat. Just as low CSE groups will be risk-averse, when high levels of threat interact

with low CSE groups the level of risk-aversion increases. The high levels of threat will decrease

information search while simultaneously increasing the levels of anxiety within the group. This

will lead to the well- learned risk-averse responses that the group has regressed to in the past.

First, the group polarization that increases the level of risk-aversion initiated by the low CSE

group will only be exacerbated by the high levels of threat experienced by the group. Moreover,

when high levels of threat interact with a predisposed position, threat amplifies the tendency of

the group beyond that of group polarization. However, threat will only exacerbate risk-aversion

if the group makes internal attributions for the threat (Harrington et al., 2002).

Proposition 3: CSE, structure, and threat will interact, such that the most risky decisions

will be made by high-CSE groups with internal attributions for threat, whereas the least

risky decisions will be made low-CSE groups with internal attributions for threat

DISCUSSION

Conceivably the most significant contribution of this paper is that, through a concurrent

investigation of formerly unconnected streams of research, we have suggested gaps in the

decision making literature that need to be addressed. Even though the preexisting fragmented

state of research on risk-seeking and non risk-seeking behaviors were not conducive to be readily

identified, the proposed model has perhaps provided a reformulated theory that is more complete

and parsimonious than previous theories. The analysis presented in this paper thus advances the

understanding of deviations from rational decision making by suggesting that interactions among

various decision making factors can increase the likelihood of behaviors that do follow the basic

tenets of utility theory.

The theory of risk behavior propositioned here builds directly on current theories of risk-

seeking and non risk-seeking behaviors in illuminating individual risk behavior. Academics have

previously illustrated the roles of individual differences (Driver, Brousseau, & Hunsaker, 1990;

Rowe & Mason, 1987; Whyte, Saks, & Hook, 1997), structural factors (Fredrickson, 1986;

Gigone & Hastie, 1997; Libby, Trotman, & Zimmer, 1987; Sniezek & Henry, 1989), and

environmental factors (Harrington et al., 2002; Staw et al., 1981). Therefore, one contribution of

this paper is that it draws together these previously unrelated streams of research and

demonstrates how they offer the groundwork for a theoretical model of risk-seeking and non

risk-seeking behavior that is more comprehensive and accurate than prior theories.

One of the reasons for formalizing the proposed theory in the form of an interactive

model is to facilitate cumulative empirical research in this area. In part, this is in response to the

observation that a great deal of has been learned within relatively narrow specialized subareas of

risk behavior and non risk behavior, but that there has been little integration across the

historically discrete theoretical perspectives. The ideas proposed in this paper are meant to

provide preliminary evidence of the value of such cross-specialty research, and it is hoped that

this framework can stimulate additions, revisions, and challenges to this analysis. By attempting

to delineate more explicitly the different constructs and theories about their interactive

relationships, the goals here are to provide a broader and more coherent framework for designing

empirical research on risk-seeking and non risk-seeking that can clearly and effectively

distinguish these important variables.

The combination of various theoretical perspectives (e.g.) implies that future empirical

research should not merely examine isolated cells in a two-by-two matrix (Sitkin & Pablo, 1992),

but should modify completely individual, structural, and environmental dimensions to provide a

test of ideas proposed here as well as the theories and empirical findings on which they are

based. Consequently, this paper responds to the call for the development of theories that can

concurrently investigate the effects of disposition (individual differences) and situations

(structure and environment) (Davis-Blake & Pfeffer, 1989). Additionally, it is essential for future

empirical studies to reflect the operational intricacy of the constructs presented in this paper,

taking into account the importance of the numerous variables of individual, structural, and

environmental in a systematic and valid approach.

Future research on interaction terms

There are many additional plausible interaction effects suggested by the proposed model.

This limitation, however, suggests another way by which researchers could extend the ideas

proposed herethrough the theoretical evaluation and empirical testing of possible interaction

effects among the independent variables in Table 1. Researchers interested in specialized

subareas of risk-seeking, escalation of commitment, and risk-aversion may choose to focus on

smaller sets of variables so as to address the possible interaction effects among them.

CONCLUSION A sizeable body of prior theoretical and empirical research appeared to support the

primary influence of objective or perceived interactional effects of individual differences,

structural, and environmental factors on risk-seeking and non risk-seeking behaviors. Yet the

reconceptualization presented in this paper suggests that this earlier work and the seemingly

unconnected results it generated can be explained by a theory in which the determinants of

deviations from rational decision making interact to form new decision making dynamics. By

providing a single, integrated and interactive model of the determinants of deviations from

rational decision making, this paper not only draws together conclusions of a number of theories

that have not previously been compared, but also highlights opportunities of for future theoretical

and empirical work.

As should be noted in Table 1, the potential opportunities for research on this topic are

virtually limitless. Furthermore, the empirical testing among the various factors would be

extremely beneficial for the field, as not much has been done to date. By testing the interaction

of assorted variables from the individual differences, structural, and environmental columns,

research on decision making could make quantum leaps in our field.

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Table 1 Determinants of Decision Making

Individual Differences Structure Environment Core Self-Evaluations Individual vs. Team Threat

Core External Evaluations Organizational Structure: Vertical vs. Flat

Past Performance

Five Factor Model of Personality

Organizational Structure: Mechanistic vs. Organic Politics

Individualism/Collectivism Organizational Structure: Divisional vs. Functional Technology

Attribution Style/Biases Rewards (agency issues) Dynamic vs. Static (Time) Myers-Brigg Type Indicator

(MBTI) Hierarchical Teams vs. Self-

Managing Work Teams Innovative vs. Mature

Affective Disposition Level of Empowerment Cultural Risk Values

Social Skill Organizational Control Systems

Leader Risk Orientation

Political Skill Team Composition Problem Familiarity Risk Preference, Risk

Perceptions, Risk Propensity Size Social Influences

General Decision Making Style (GDMS) Satisficing vs. Maximizing Level of Uncertainty

National/Cultural