Integrating Theories of Motivation 1 Running head: INTEGRATING THEORIES OF MOTIVATION Integrating Theories of Motivation

Progress towards understanding human behavior has been hindered by discipline-bound theories, dividing our efforts. Fortunately, these separate endeavors are converging and can be effectively integrated. Focusing on the fundamental features of Picoeconomics, Expectancy, Cumulative Prospect Theory, and Need Theory, Temporal Motivational Theory (TMT) is constructed. TMT appears consistent with the major findings from many other investigations, including psychobiology. Potential applications of TMT are numerous, including: consumer behavior, aggression, stock market, and governmental behavior. Integrating Theories of Motivation 3 The fields of economics, decision-making, sociology, and psychology share a common desire to understand human nature. This extensive, multidisciplinary interest in establishing who we are reflects the enormous ramifications of the endeavor. As Pinker (2002) catalogues, theories of human nature have been used to direct relationships, lifestyles, and governments – with disastrous effects when based on faulty models. On a smaller applied scale, treatments, training, compensation, and selection all depend upon our theories of human behavior. Even the overtly physical enterprise of job design can require positing human constants such as “growth need strength” (Hackman & Oldman, 1976). To ensure the efficacy of our interventions, we need to determine what describes, drives, or decides our actions. Ironically, our understanding of behavior has been hindered by the very extent of our efforts. There is a superabundance of motivational theories. Not only does each field have its particular interpretation, but there are ample subdivisions with each discipline. Psychology, for example, has the traditions of selfregulation, motivation, and personality, each with its own nomenclature, structure, and etiology. These subdivisions necessarily divide our efforts, limiting the extent to which insights can be shared. This problem has recently been recognized and lamented by many prominent researchers (e.g., Barrick & Mount, 1991; Judge & Ilies, 2002; Elliot & Thrash, 2002), but it is by no means a new issue. Consider the words of the Irving Fisher (1930: 312), the venerated economist, which are regrettably still far too relevant: “The fact that there are still two schools, the productivity school and the psychological school, constantly crossing swords on this subject [time preference/implicit interest rates] is a scandal in economic science and a reflection on the inadequate methods employed by these would-be destroyers of each other.” Integrating Theories of Motivation 4 Fortunately, our theories also have several strong commonalties, and their effective integration seems achievable (Larrick, 1993; Mischel & Shoda, 1999). If it were possible to effectively combine these different conceptions of human nature, we would have substantially progressed towards a common theory of basic motivation. To use E. O. Wilson’s term, this convergence is an excellent example of consilience. Consilience is “a ‘jumping together’ of knowledge by the linking of facts and fact-based theory across disciplines to create a common groundwork of explanation” (1998: 8). If a theory can be shown to have consilience, its scientific validity is vastly improved as it represents different avenues of inquiry coming to similar conclusions. To this end, we integrate four closely related motivational theories, using the insights of each to inform the other. We start with Picoeconomics (Ainslie, 1992), which we then subsequently extend with Expectancy Theory (e.g., Vroom, 1964), Cumulative Prospect Theory (Tversky & Kahneman, 1992), and Need Theory (e.g., Dollard & Miller, 1950). It is important to note that none of these theories are definitive, each containing various limitations. However, we are not attempting a full integration of their every detail, but focus on linking together these theories’ most enduring and well accepted features. One of the most important of these features is time. Time is a critical component of choice or motivated behavior. As Luce (1990: 228) notes, “quite clearly any empirical realization of a decision tree has a strong temporal aspect...” and the failure to include time “...is a clear failing of the modeling.” Similarly, Kanfer (1990) critiques theories that are episodic, and thus have difficulty accounting for behavior over time and events. Fortunately, time or delay does feature in several motivational formulations, its application is consistent where included, and through integration it can be extended to other theories where it Integrating Theories of Motivation 5 was previously absent. Consequently, we label the outcome of our integrative efforts Temporal Motivational Theory (TMT) because of its emphasis on time as a motivational factor. We then show that TMT is corroborated with the major findings from Psychobiology and demonstrate how it can account for the findings from another motivational theory altogether, Goal Theory (Locke & Latham, 1990).We also use Temporal Motivational Theory to explain procrastination, a prototypical performance problem. As a general theory of human behavior, the applications of Temporal Motivational Theory are numerous. We identify four diverse areas that might benefit by employing it in specific ways. Also, we note that this model of human behavior, like all models, must strike a balance between precision and parsimony. Some refinements may add undue complexity while accounting for only minimal incremental variance. Still, there are promising insights and extensions that should be considered, and we review two of them. Finally, future research on TMT may choose to exploit two powerful but underused venues: a Computerized Personal System of Instruction and computer simulations. TEMPORAL MOTIVATIONAL THEORY To develop Temporal Motivational Theory (TMT), we consider four related understandings of human nature: Picoeconomics, Expectancy, Cumulative Prospect Theory, and Need Theory. These four postulations are particularly well suited for consolidation as they reflect common sources in their development and thus share many terms. Consequently, areas of overlap are quite definite. Furthermore, they can be expressed formulaically, allowing their integration with minimal translation. Though many of their aspects are evident in other theories, as will be discussed later, these four are sufficient to develop TMT and fit together in a relatively Integrating Theories of Motivation 6 straightforward manner. We start with picoeconomics as it, of all the theories considered, has time as its most central feature. Picoeconomics or Hyperbolic Discounting Ainslie (1992), under the title of Picoeconomics, and Ainslie and Haslam (1992), under the title of Hyperbolic Discounting, discuss a theory that helps to account for choice of behavior over time. The theory already demonstrates considerable consilience, drawing support from a variety of research literatures including sociology, social psychology, psychodynamic psychology as well as behaviorist psychology and economics in particular. In its basic form, the theory is simple. Essentially, people are beset with choosing among a variety of possible rewarding activities. In choosing among them, there is an innate tendency to inordinately undervalue future events. We tend, then, to put off tasks leading to distant but valuable goals in favor of ones with more immediate though lesser rewards. Inevitably though, time marches on and as the once future events loom ever closer, we see their value more clearly. Eventually, we experience regret if we have irrationally put-off pursuing this more valuable goal to the extent that it can no longer be realistically achieved. Going beyond this qualitative description, the theory of picoeconomics tries to express the effects of temporal discounting mathematically. Summarizing the efforts from behaviorist and economic perspectives, Ainslie (1992) notes several attempts to provide an accurate equation. Of these, the matching law is one of the first and simplest (Chung & Herrnstein, 1967). The matching law considers how frequency, magnitude, and delay of reinforcement affect choices, with delay being the critical feature. It is the dominant model describing choice among various concurrently administered, variable interval schedules (Ainslie, 1992). In other 1 This matching law can be further decomposed into even more basic behaviorist principles (Herrnstein, 1979), specifically invariance and relativity. Integrating Theories of Motivation 7 words, when we must choose between several courses of action that all result in a reward, albeit at different times, this model best predicts the aggregate behaviors of adults (see Myerson & Green, 1995). Similarly, a related version of this law used in the economic field also shows extremely strong validity (see Lowenstein & Prelec, 1992). The simplest version of the matching law contains just four components: Rate Amount Utility Delay × = Utility indicates preference for a course of action. Naturally, the higher the utility, the greater the preference. The next three variables reflect aspects of the reward or payout of the action. Rate indicates the expectancy or frequency that the action will lead to the reward. It ranges from 0% to 100%, with 100% reflecting certainty. Amount indicates the amount of reward that is received upon payout. Essentially, it indicates the magnitude of reinforcement. Finally, delay indicates how long, on average, one must wait to receive the payout. Since delay is in the denominator of the equation, the longer the delay, the less valued the course of action is perceived. There also have been several modifications to the basic matching law. Rate is often dropped since it can largely be expressed in terms of delay alone; rewards delivered at lower rates necessarily create longer average delays. Also, a new parameter is typically included to capture individual differences regarding sensitivity to delay. The greater the sensitivity, the larger the effect delays have upon choice. Of all these modifications, Mazur’s (1987) equation is likely the simplest and most widespread. It posits: ( ) Amount Utility Z T t = + Γ − Aside from dropping rate, there are three changes from the original matching law. T – t refers to the delay of the reward in terms of “time reward” minus “time now.” Γ refers to the subject’s Integrating Theories of Motivation 8 sensitivity to delay. The larger Γ is, the greater is the sensitivity. Finally, Z is a constant derived from when rewards are immediate. It prevents the equation rocketing towards infinity under periods of small delay and thus, in Shizgal’s (1999) terminology, can be considered the determinant of “instantaneous utility.” In addition, the reciprocal of this equation can be used to predict preferences among punishers instead of rewards (Mazur, 1998). Consequently, people prefer distant punishers to more instant ones. There have been several other attempts to further refine this equation, but without established success. For example, explorations into using other mathematical expression (e.g., Logue, Rodriguez, Pena-Correal, & Maruo, 1984), particularly exponential functions, tend not to be as accurate (Green, Myerson, & McFadden, 1997; Mazur, 2001), though they are still favored in economic circles due to their close resemblance to a purely rational discount model. In economics, this phenomenon is studied under the rubric of time preference or implicit interest rate (Antonides, 1991). Insert Figure 1 about here Figure 1 outlines picoeconomics by displaying the utility curves for two courses of action: saving or spending an expected financial bonus. From a distance, both options are effectively discounted and the benefits of saving appear superior. However, when the bonus is received from the employer, the benefits of spending are immediate while saving benefits remain distant. Due to temporal discounting, people likely find themselves changing their original intentions, and this crossing of utility lines reflects the well established phenomenon of 2 For example T t uτ τ τ δ = ∑ where uτ is a person’s instantaneous utility in period t and δ is the discount factor for one period (Lowenstein & Prelec, 1992; O’Donoghue & Rabin, 1999). Integrating Theories of Motivation 9 preference reversal (Ainslie, 1992; Lowenstein & Prelic, 1992; Steel, 2003). What is planned today does not always turn into tomorrow’s actions. Expectancy Theory Expectancy Theory, or Expectancy x Value (E x V) theory, represents an extensive family of individual formulations. Vroom (1964) first introduced the notion to industrial organizational psychology, but it has an earlier history in the cognitive field (e.g., Rotter, 1954) that in turn can be predated by economic investigations under the rubric of subjective expected utility (Bernouli, 1738 as cited in Savage, 1972/1990). In essence, E x V theories suggest that a process akin to rational gambling determines choices among courses of action. For each option, two considerations are made: i) what is the probability that this outcome would be achieved, and ii) how much is the expected outcome valued? Multiplying these components, expectancy and value (i.e., E x V), and the action that is appraised as largest is the one most likely to be pursued. A major limitation to E x V models is that they are episodic, and as mentioned, have difficulty accounting for behavior over time (Kanfer, 1990). This limitation may partially explain Van Eerde and Thierry’s (1996) meta-analytic finding that E x V often predicts behavior over time rather weakly and significantly less well than one’s intention to perform. Fortunately, its incorporation into a hyperbolic discounting model largely rectifies this weakness. As mentioned, the numerator of the original matching law was composed of two terms: amount and rate. Respectively, these terms are equivalent to value and expectancy, reflecting a shift from a behavioral to a cognitive standpoint. The behaviorist view expresses the equation’s variables in terms of what should be objectively observed. The cognitive view recognizes that the impact of all the variables is not uniform but depends upon interpretation differences among individuals, though the difficulty in determining these differences may be extreme. Integrating Theories of Motivation 10 Consequently, amount is more accurately described in cognitive terms as the perceived magnitude of reward. It reflects a subjective evaluation, dependent upon an individual’s perception. Similarly, rate refers to the frequency that actions lead to rewards or, alternatively, the probability of acquiring the expected outcome. By describing amount as value and returning rate to the equation in the form of expectancy, picoeconomics begins to encapsulate expectancy theory. The final equation should be: ( ) Expectancy Value Utility Z T t × = + Γ − Of course, other modifications can be argued from expectancy theory. For example, Vroom (1964) broke expectancy down into two components: expectancy and instrumentality. In this case, expectancy refers to whether the intended course of action can be completed successfully. Instrumentality refers to whether, having been successful, the expected rewards would be forthcoming. Research indicates, however, that this modification may be detrimental to predicting behavior rather than helpful (Van Eerde & Thierry, 1996). Many other refinements have been proposed, including terms that account for resource allocation (e.g., Kanfer & Ackerman, 1996; Naylor, Pritchard, & Ilgen, 1980) and future orientation (e.g., Raynor & Entin, 1982). Regardless of the individual formulation, E x V is the core aspect. Cumulative Prospect Theory Tversky and Kahneman’s (1992) Cumulative Prospect Theory (CPT), an update of Kahneman and Tversky’s (1979) Prospect Theory, is a descriptive model closely related to traditional expectancy theory, particularly Atkinson’s (1957) formulation. Often described as one of the leading theories of decision (e.g., Fennema & Wakker, 1997; Levy 1992), CPT seeks to describe choice under uncertainty by reconsidering how value is derived as well as how expectancy should be transformed. Here, only the pertinent aspects of CPT are reviewed: full Integrating Theories of Motivation 11 discussion of the original and cumulative version of prospect theory requires more attention than can be easily provided, though it is available elsewhere (see Fennema & Wakker, 1997; Tversky & Kahneman, 1992). Also, for a relevant and recent psychological example, see Hunton, Hall, and Price (1998) who applied original prospect theory to the value of “voice” in participative decision-making. Focusing on its key theoretical elements, CPT is very similar to the original Prospect Theory. Acknowledging considerable variability across people, both theories codify regularities in how we interpret values and expectancies. First, values are based on outcomes that are defined as losses and gains in reference to some status quo or baseline. These outcomes are transformed following a function that is concave for gains, convex for losses, and steeper for losses than for gains. In other words, ‘losses loom larger than gains.’ Second, probability (i.e., expectancy) is also transformed following a function that has both convex and concave segments. Lower probabilities tend to be convex (i.e., overweighted) while higher probabilities tend to be concave (i.e., underweighted). Similar to the determination of values, the exact parameters for the transformation of probability differ for losses and gains. Consequently, the expected utility of any behavior is based on considering the combined utility of its possible gains and possible losses, with gains and losses each being estimated differently. Insert Figures 2 & 3 about here 3 Mathematically, both the transformations for value and expectancy create curves reflecting logarithmic functions, notably similar to Fechner’s law (1860/1966) describing just noticeable perceptual differences. Fechner’s law states that given x amount, you will notice a change of x ∆ that allows k to remain a constant, as in: x x k ∆ = . To be precise though, Tversky and Kahneman (1992) actually use a related but exponential form of psychophysical scaling called Steven’s law (see Figure 2). Similarly, expectancy is also modeled using an exponential function (see Figure 3). Integrating Theories of Motivation 12 By itself, CPT suffers the same limitation as Kanfer (1990) pointed out in expectancy theory, i.e. failure to include time as a variable. Consequently, other researchers have already proposed various integrations of prospect theory with some hyperbolic time-discounting function (Lowenstein & Prelec, 1992; Rachlin, 1990; Schouwenburg & Groenewoud, 1997). Given this foundation and CPT’s similarity to expectancy theory, only two equations are needed to incorporate CPT into picoeconomics. 1 1 ( ) ( ) + k n CPT CPT CPT CPT i i k E V E V Utility Z T t Z T t + − = = + × × = + + Γ − + Γ − ∑ ∑ For any decision, one considers n possible outcomes. The first term, containing + CPT E and + CPT V , reflects the transformed values for the expectancy associated with k gains and the perceived value of each of these gains. The second term, containing CPT E and CPT V , reflects the transformed values for the expectancy associated with n-k losses and the perceived value of each of these losses. Given that losses carry negative value, the second term will always diminish the first and thus the overall utility. The summation sign for each term reflects the possibility of multiple outcomes given any act and thus multiple possible gains or losses. It is this summation sign that makes CPT cumulative. Of note, though the ability to model decisions with multiple possible outcomes is a significant improvement, it takes a moment to consider how expectancy is interpreted under this model. With CPT the decision weight or CPT E is not absolute expectancy, but the capacity of events. The notion of capacity, in Tversky and Kahneman’s (1992: 301) words, “can be interpreted as the marginal contribution of the respective event.” To combine all possibilities effectively, each outcome is evaluated inc rementally, that is relative to the value of other outcomes. For example, the expectancy weighting for any positive event is the chance of it or an Integrating Theories of Motivation 13 even better outcome occurring, minus the chance of just an even better occurrence (e.g., 40% 30% = 10%). It is helpful to keep in mind the simple circumstance where only one positive outcome and/or one negative outcome is considered. In this case, the capacity of each outcome is equal to CPT E and the equation is more readily interpretable as no summation is necessary. Further discussion of capacity is available in the articles of Fennema and Wakker (1997) and, of course, Tversky and Kahneman (1992). Need Theory One of the earlier psychological theories is Murray’s (1938) system of needs. As a whole, it somewhat dated, but key aspects endure in modern personality theory (Tellegen, 1991). We briefly review these fundamental components. To begin, needs represent an internal energy force that directs behavior towards actions that permit the satisfaction and release of the need itself. It is what drives us to do whatever we do. Needs can be primary or viscerogenic, directly related to our biological nature (e.g., the need for food), or they can be secondary or psychogenic, related to our personality. Of these secondary needs, Murray initially guessed that around 20 might exist, though Winter (1996) suggested that only three are fundamental: need for achievement, need for affiliationintimacy, and need for power. Need for achievement is deriving pleasure from overcoming obstacles, need for affiliationintimacy is deriving pleasure from socializing and sharing with people, and need for power is deriving pleasure from gaining strength or prestige, particularly by affecting other’s well-being. These needs are not stable, but tend to fluctuate in intensity, ranging from a slumbering satisfaction to an absolute craving. Our behaviors are ruled partly by need intensity. At any time, the need that is the most intense is the one we attempt to satisfy or to reduce through our thoughts and behavior. Thus, our actions represent our needs. Of most importance, need intensity can be influenced by external Integrating Theories of Motivation 14 cues, described as press. Press occurs when we encounter situations that we expect have a good chance of soon satisfying a need, and consequently the salience and intensity of that need becomes acute. Of note, press has strong commonalities with many modern and well established psychological constructs. In a comprehensive review of the construct, Tellegen (1991) connects press to several other theories (e.g., stimulus-response) and theorists (e.g., Allport, 1961). These aspects of need theory share numerous strong commonalities with our previous formulations. First, need intensity appears analogous to utility. In the same way we pursue actions that most reduce our strongest need, we also pursue actions that provide the most utility. Needs are related to value, helping to determine the actual value that outcomes have. Finally, press is essentially a combination of expectancy and time delay. As will be discussed, others have reviewed these connections in great detail. To some extent, need theory can be further integrated through the works of McClelland (1985) as well as Dollard and Miller’s (1950). McClelland reviews the theories of Atkinson (1964), who provides a classic formulation of expectancy theory, as well as Hull (1943), who provides some of the most influential formulations of behavior theory by far (Schwartz, 1989). Of note, behaviorism is, as mentioned, the basis of the original matching law of Chung and Herrnstein (1967). Core aspects of Atkinson’s and Hull’s theories are virtually identical, both ultimately using expectancy by value frameworks that differ fundamentally only in nomenclature. For example, in place of utility, Hull indicates excitatory potential (sEr) while Atkinson uses tendency to achieve success (Ts). In place of expectancy, Hull refers to habit 4 There has been criticism that the drive or need reduction is a somewhat simplified view of reinforcement, and in a detailed review, Savage (2000) concludes that this is true. However, Savage also notes that as a general concept, it has proven invaluable for organizing a wide range of motivational states, which is consistent with its use here. Also, see McSweeney and Swindell (1999) who recently revitalized the role that need theory may play in motivation. Integrating Theories of Motivation 15 strength (sHr) while Atkinson uses probability of success (Ps). Finally, in place of value, Hull refers to a combination of drive (D) and incentive (K) while Atkinson uses motive strength (Ms) and incentive value (INs). Of note, in McClelland’s terms, Ms for success is equivalent to need for achievement. In addition, Atkinson proposes that the utility of any achievement-oriented situation is determined by two individual difference factors: the need for achievement and the need to avoid failure. The effect each need has on overall utility is calculated separately, as with losses and gains in CPT, with the resulting value indicating the tendency to pursue achievement. Dollard and Miller (1950) provide even greater connection. They also attempt to describe some of the conflicts observed with psychodynamic drives or needs through behaviorism. Consistent with the concept of press, Dollard and Miller note that drive strength increases as we get closer to the realization of our goals. This, they explain, is due to the combined effect of two, more basic, principles of behaviorism, the gradient s of reinforcement and of stimulus generalization. The gradient of reinforcement reflects the temporal aspect, i.e. the more immediately rewards and punishment are expected, the greater their effects. The gradient of stimulus generalization is akin to the element of expectancy. Environmental cues best create approach and avoidance behavior when they reliably predict the occurrence of rewards and punishments. So far, need theory appears to be derived from the same fundamental features as picoeconomics, expectancy, and cumulative prospect theory (CPT). Behavior is determined by need strength (Utility), and long-term considerations (Delayed) are only relevant to the extent they affect its present intensity. However, need theory does contain one unique contribution. Presently, the discounting constant, Γ, is treated as identical for both losses and gains. However, 5 Highlighting their similarity, Weiner (1990: 619), while reviewing the his tory of motivational research, notes that “there was some contentment merely in eliminating the term drive and replacing the notion of habit with that of expectancy.” Integrating Theories of Motivation 16 Dollard and Miller (1950) suggest that this increase in drive occurs at different rates for different needs. In their words, “the strength of avoidance increases more rapidly with nearness than does that of approach. In other words, the gradient of avoidance is steeper than that of approach” (1950: 352). More recent research, as reviewed by Trop and Liberman (2003), suggests the opposite though, that losses actually are discounted less steeply than gains. Despite these differences, both these results commonly indicate that Γ should not be kept at a constant, but should differ for gains and losses. Consequently, our formula is revised in this fashion: 1 1 ( ) ( ) + k n CPT CPT CPT CPT i i k E V E V Utility Z T t Z T t + − + − = = + × × = + + Γ − + Γ − ∑ ∑ With this final modification, we have constructed Temporal Motivational Theory. It is an assimilation of the common and unique fundamental features across our four target theories. Of its elements, only value consistently appears, though most other aspects are multiply supported. Expectancy occurs in each theory except picoeconomics. Temporal discounting features in picoeconomics and need theory (i.e., press). Losses and gains are separately calculated in both CPT and need theory. This convergence provides considerable consilience for Temporal Motivational Theory (TMT) and thus necessarily demonstrates validity. That is, when different research traditions come to approximately identical conclusions, results gain in credibility. PSYCHOBIOLOGICAL THEORY The four theories outlined here indicate that motivation can be understood by the effects of expectancy and value weakened by delay, with differences for rewards and losses. However, as mentioned, they share a variety of common sources in their development, particularly behaviorism. It would be useful to find corroboration for TMT from an entirely different standpoint. To this end, psychobiology can provide such validation. Integrating Theories of Motivation 17 Relatively recently, there have been great advances towards identifying the biological basis of motivation, and one of the most accepted of these attempts is Gray’s theory (1982, 1987, 1991, 1994). Gray, building on earlier animal research, proposes that much of human behavior is due to two separate systems: the behavioral activation system (BAS) and the behavioral inhibition system (BIS). The workings of the BAS and the BIS are often described in terms of impulsiveness and show remarkable similarities to TMT’s discounting function for gains and losses. Gray has not labored alone, though. Several other researchers have impressive research programs specifically connecting utility appraisals to a physiological substrate. For example, Ito and Cacioppo (1999) consider the basis of Γ and value while Drake (1987) investigates the nature of expectancy. Also, several psychopharmacology practitioners have been particularly interested in determining and affecting the bodily processes leading to impulsiveness/temporal discounting. As will be shown, all this work supports the basic structure of TMT. To demonstrate this corroboration, Gray’s theory will be reviewed and then extended through a consideration of these other bodies of research (e.g., Drake, 1987; Ito & Cacioppo, 1999). In Gray’s model, the BAS is an anatomical structure located in the septal and lateral hypothalamus areas of the brain. Considerable research links its functioning to the neurotransmitter dopamine (see Hoebel, Rada, Mark, & Pothos, 1999), and those with increased dopamine production should have a more active BAS. An active BAS emphasizes “approach,” helping to increase sensitivity to imminent potential rewards, i.e., to cues of impending 6 Though not at a physiological level, Monterosso and Ainslie (1999) theoretically related impulsiveness to Γ, the general discounting term, and several others have gathered self-report data that empirically supports their affinity (Madden, Petry, Badger, & Bickel, 1997; Ostaszewski, 1996, 1997; Petry, 2001; Richard, Zhang, Mitchell, & de Wit, 1999). 7 Hoebel et al.’s (1999) research, aside from supporting the importance of dopamine, adds some fine physiological detail. For example, it summarized evidence that indicated the neurotransmitter acetylcholine has a role in the inhibition of behavior; its release helps to create satiation. Integrating Theories of Motivation 18 incentives. Consequently, as the BAS increases in strength, people tend to become impulsive, discounting future repercussions to pursue what is readily available. On the other hand, the BIS is primarily located in the brain’s septo-hippocampus. Strong evidence links it to the neurotransmitter serotonin (Coscina, 1997), though the task of determining its physical details remains. Those with low levels of serotonin should show a more active BIS. Whereas the BAS was associated with “approach,” the BIS is associated with “inhibition” or “avoidance.” People with an active BIS are sensitive to imminent potential punishers, to cues of impending threat. Though the term “impulsiveness” is sometimes reserved to describe the BAS exclusively, the word is also applicable to the BIS, especially in its discounting sense. Also, Barratt (1993) reviews research that specifically connects impulsiveness to serotonin, the neurotransmitter of the BIS. Thus, when the BIS is strong, people should act impulsively, discounting future repercussions to avoid present dangers. A variation of Gray’s dichotomy can be found in Ito and Cacioppo’s (1999) “Bivariate Model of Evaluative Space.” Ito and Caccioppo conclude that utility evaluations are understandable from a bivariate rather than a univariate model. By bivariate model, they refer to separate positive and negative motivational systems responses for appetite and aversion respectively. The parameters for each of these motivational systems are different, including a sharper slope for negative stimuli, thus supporting Dollard and Miller’s (1950) contention that the avoidance gradient is indeed steeper. Also, they note an onset bias for positive stimuli; a positive onset bias refers to a positive intercept in neutral situations, that is, there will be a slight tendency for approach behavior when the situation appears otherwise motivationally balanced. Their support for this model is extensive, using information derived from a long list of methodologies: event-related brain potentials ; EEG asymmetry; startle eyeblink modulation; Integrating Theories of Motivation 19 facial electromygraphy, and autonomic activity. Interestingly, they themselves notice the similarities between this bivariate model and Kahneman and Tversky’s (1979) as well as Dollard and Miller’s (1950) work, both previously discussed. This bipartition of positive and negative appears to continue into the realm of expectancy as well. Zuckerman (2001) summarizes considerable research indicating that optimistic and pessimistic expectations do indeed seem to be rooted in separate biological mechanisms. The work reviewed is extensive, ranging from twin studies to psychopathology, but not included in Zuckerman’s synopsis is a series of revealing studies by Drake (1984, 1985, 1987; Drake & Ulrich, 1992). Drake was able to manipulate which brain hemisphere was primary in the ratings of confidence. He found that participants who had their left hemisphere activated rather than their right were more optimistic, especially regarding risky decisions. In conjunction with Richard Davidson’s research, this is highly significant. Davidson (1994), in a summary of his work on this topic, indicates that the anterior region of the left hemisphere is associated with approach-related positive affect while the same region of the right hemisphere is associated with withdrawal-related negative affect. Consequently, it appears that expectancies for gains and losses are derived somewhat independently, exactly as expected. Finally, the journal of Psychopharmacology recently dedicated an entire issue to the construct of impulsiveness and temporal discounting. Consistent with Barratt’s (1993) review, Evenden (1999) notes that serotonin has been connected to impulsive behavior since at least 1986 and Soubrié’s research. This would indicate that the BIS rather than the BAS, as is typically contended, is the more relevant system. However, research indicates that impulsiveness is affected by a variety of different pharmacological interventions, each affecting different aspects of the brain and its systems. (Ho, Mobini, Chiang, Bradshaw, & Szabadi, 1999). Of these Integrating Theories of Motivation 20 different systems, the prefrontal cortex plays an especially important role in preventing impulsive behavior and is particular susceptible to dopamine depletion (Jentsch & Taylor, 1999; Wade, de Wit, & Richards, 2000). Of note, several of these researchers use hyperbolic discounting, a key feature of TMT, to explain their results (e.g., Evenden, 1999; Ho et al., 1999). In summary, psychobiology supports Temporal Motivational Theory as a motivation model. There appears to be separate brain mechanisms that are analogous to expectancy, value, and time. Each of these three components appear to further divisible into positive and negative or approach and avoidance. Of particular relevance, psychobiological researchers themselves note how their findings support hyperbolic discounting, prospect theory, and need theory (i.e., Dollard & Miller, 1950). INTEGRATION OF TEMPORAL MOTIVATIONAL THEORY The relationship between Temporal Motivational Theory and Picoeconomics, Expectancy, Cumulative Prospect Theory, and Need Theory is largely that of simplicity. The latter theories are simplifications of TMT, focusing on fewer terms or eliminating idiographic variation. However, they also have some unique features and tend to explore the aspects they do consider in greater depth. For example, only need theory closely examines the role of satiation. Consequently, their commonalities do not necessarily make them redundant. Similarly, there are other theories that share several aspects with TMT. Though each of them possesses unique applications and nuance, there is sufficient overlap to provide consilience. Here, we briefly note TMT’s similarity with several prominent motivational and personality theories. Following this, we interpret Goal Theory within a TMT framework in more depth. Integrating Theories of Motivation Integrating Theories of Motivation 21 Of Temporal Motivational Theory’s fundamental features, three reappear across several motivational models: approach/avoidance dichotomy, E x V, and needs. The first of these, an approach/avoidance dichotomy, is the most widespread with Elliot and Thrash (2002) as well as Carver, Sutton, and Scheier (2000) noting a confluence of findings from a variety of motivational formulations that support its existence. This includes the Big Five personality model, where extraversion and neuroticism appear to be reflections of the BAS and BIS, respectively. Also, Kuhl’s (2000) Personal Systems Interaction Theory can be understood as the explicit examination of two separate motivational systems, one associated with positive affect that facilitates action and one associated with negative affect that inhibits action. Regarding expectancy and value, several theories appear to draw upon these elements. To begin with, Bandura (1997) integrates Ajzen’s (1991) Theory of Planned Behavior into the traditional E x V framework, indicating that it is partly a simplification of TMT. In turn, SelfEfficacy Theory, which has been championed by Bandura, is closely related to expectancy, if not identical in some respects (Bandura & Locke, 2003; Skinner, 1996; Vancouver, Thompson, & Williams, 2001). Also, Gollwitzer (1996: 289), when discussing his Model of Action Phases, states, “preferences are established by employing the evaluative criteria of feasibility and desirability.” Plainly, feasibility is related to expectancy while desirability is a form of value. Finally, incorporating needs into TMT provides us another avenue to reflect the influential Big Five personality model. Specifically, personality traits appear to be the behavioral expression of needs, especially needs as measured by questionnaire (Winter, John, Stewart, Klohnen, & Duncan, 1998). Consequently, we tend to be extraverted because of a need for affiliation and conscientious because of a need for achievement. Also, in a recent meta-analytic Integrating Theories of Motivation 22 review, Judge and Ilies (2002) provide some connection between traits and the constructs of expectancy and self-efficacy. It is important to note that these motivational theories have less derivable features, such as examining how mindsets change during the decision-making process. However, these elements tend to complement, rather than contradict, TMT. Emotions are one such instance. As was previously mentioned, emotions can be largely (though not entirely) decomposed into a positive and negative affect framework (Davidson, 1994). Reviewing the effect of positive affect on decision-making, Isen (2000) notes how it appears to affect our expectancy and value functions. Specifically, those in a good mood tend to increase their estimated probability of success but also tend to fear loss to a greater degree (i.e., losses loom even larger). Integrating Goal Theory One of the most widely used motivational theories within an industrial/organizational context is Goal Theory (Karoly, 1993), and for good reason. Extensive study unambiguously indicates that goal setting is an extremely powerful selfregulatory technique (see Lock & Latham, 2002 for a recent review). However, there is less consensus regarding why it works. Typically, it is thought to affect performance through four mechanisms: a directive function (attention); an energizing function (effort); a strategic function (developing plans); and an increase in persistence. These explanations have been criticized on the basis that that “each of these constructs is really very complex requiring the use of several other constructs only vaguely implied from the descriptions”(Naylor & Ilgen, 1984: 101). If Temporal Motivational Theory is valid, it should be able to help account for the efficacy of goal setting as well as three Integrating Theories of Motivation 23 characteristics that further modify this relationship (Bandura, 1997): challenge, specificity, and proximity. 8 The effectiveness of goal setting can be largely explained by two aspects of TMT: the law of diminishing returns (see Figure 2) and temporal discounting (see Figure 1). Any division of a project into several smaller and more immediate sub-goals appears to takes advantage of these two elements. As mentioned, perceived value has a curvilinear relationship to a more objective assessment. Substantial divisions of large goals may result in a series of sub-goals, each valued only slightly less than that of the original whole. For example, though completion of an entire project may best satisfy one’s need for achievement, each intermediate step also temporarily satiates. Importantly, each of these smaller sub-goals can be completed sequentially, allowing them to be realized more quickly. This state of affairs presents a potent motivational opportunity. Research has shown that the parsing of situations affects decision-making. For example, Rachlin (1990) discusses how gambling behavior is influenced by whether people consider a period of betting as several individual bets or just a single gambling session. 9 By subdividing a large project into smaller goals, the sum of the parts can be greater than the whole (to reverse a popular aphorism). Essentially, goal setting increases the duration of motivational dominance, when drive towards a course of action is likely to supercede competing options. This effect is exemplified in Figure 4, where a person has 90 days to finish a project. Actions towards a goal occur only if its drive or utility exceeds that of other pursuits, that is, background temptations as represented by the straight dashedline. Here goal setting divides the project into three sub-goals, each valued at 8 Of note, Dörner (1989) provides an analysis of these issues very similar to that given here. As additional consilience, he operates entirely from a self-regulatory and decision-making perspective, never referring to goal theory or its associated body of research. 9 See also Dawes’ (1998) summary of sunk costs. Integrating Theories of Motivation 24 80% of the original. With goal setting, a person would find that he or she would be working toward the project for a total of 30 days. Without goal setting, it would be only 15. Insert Figure 4 about here In addition, the effect of goal setting has three moderators. First, increasing the goal’s challenge also tends to increase people’s level of effort. This factor appears to operate on two venues: choice of intensity and choice of direction. If a challenging goal is accepted, by definition it requires increased effort for achievement. Why then do people prefer pursuing them? As Bandura (1997) reviews, this is partly due to the self-satisfaction that arises from achieving the difficult rather than the easy. 10 To be effective, challenging goals should be set as they have higher value and are less easily overshadowed by other alternatives. Of note, expectancy is somewhat diminished by challenge. Consequently, there is an optimal breakpoint where the decreased expectancy of a goal outweighs the potential gains in satisfaction (Wright, Hollenbeck, Wolf, & McMahan, 1995). As Locke (1982) demonstrates, an effective goal must at least be thought to be achievable. Second, goal specificity has been shown to increase motivation. It refers to explicit standards and conditions that indicate fulfillment, aspects typically missing from “do-your-best” directives. In TMT terms, specific goals provide definite salient stimuli around which press might form (Dollard & Miller, 1950); the finish line is known. To the degree one does not have a clear understanding of when goals are about to be achieved, the motivational benefits of temporal discounting do not occur. 10 Another reason is that the achievement of challenging goals may become associated with the rewarding outcomes. As Eisenberger (1992) concludes in his revie w on learned industriousness, this follows directly from classical conditioning, where as long as effort leads to reinforcement, at least intermittently, effort will start to be perceived as reinforcing in itself (i.e., a secondary reinforcer). Integrating Theories of Motivation 25 Third, proximity of a goal affects its ability to motivate. Though Latham and Seijts (1999: 422) argue that proximity affects performance by providing “additional specific information,” TMT suggests a supporting explanation: temporal discounting. Distal goals are substantially delayed, reducing the effectiveness of expectancy and value. The only reservation regarding proximity is that by dividing a large goal into variously spaced sub-goals, each subgoal may be easier to achieve and thus less satisfying. Consequently, there is likely a breakpoint where the further subdivision of a goal decreases achievement motivation more than can be offset by the decrease in delay. AN EXAMPLE OF TEMPORAL MOTIVATIONAL THEORY Procrastination, a prototypical motivational problem, is a phenomenon that occurs in at least 95% of the population and chronically in approximately 15% to 20% of the adult population and in 33% to 50% of students (Steel, 2003). It also appears that only TMT can account for its empirical findings. As meta-analytic review indicates (Steel, 2003), the strongest correlates with procrastination are related to expectancy (e.g., self-efficacy), value, (e.g., need for achievement), and sensitivity to delay (e.g., impulsiveness). A viable theory must contain variables that address all these three elements. Furthermore, a variety of other results support the TMT model. Procrastinators demonstrate preference reversal, consistent with hyperbolic discounting. That is, they plan to work but change their minds and fail to act upon their plans. Similarly, task characteristics, such as increasing its delay or make it more averse, also predictably increases procrastination. Consequently, a simplified scenario based on procrastination is used to demonstrate how TMT relates to behavior. The archetypal setting is the essay paper for the college student. Counter to one’s original intentions, the paper is irrationally delayed and must then be completed Integrating Theories of Motivation 26 close to the final deadline, often incurring great stress and resulting in reduced performance levels. Though the writ ten assignment is given at the beginning of a semester, it is often ignored until the last few weeks or even days. From a TMT perspective, this is not surprising. As TMT predicts, we pursue whatever course of action that has the highest level of utility. Writing an essay paper is often an intrinsically aversive activity for many students; there is no delay between engaging in it and experiencing a punisher. On the other hand, the reward of achievement is relatively distant. It may not be felt until the end of the semester or perhaps even later when grades are available. To compound the matter, social activities and other temptations are readily available and intrinsically enjoyable; there is no delay in their pursuit or their rewards. Also, the aversive consequences of socializing are distant. Though indulging in them creates an oppressive backlog of work, we can usually forestall confronting the consequence until much later. Insert Figure 5 about here Consider two college student s, Jess and Jane, who have been assigned end-of-term essays at the start of a semester, September 15. The essay is due on December 15, at the end of the course. Both students like to socialize but hate to be overly stressed. Conversely, they hate to write but like to get good grades, though Jane finds good grades somewhat more important than Jess (i.e., she has a larger need for achievement). Figure 5 maps the changes in utility for these two over the course of the semester regarding their choices between studying and socializing. In the early days of the semester, socializing’s negative component is temporally distant while its positive component is in the present. This results in a high utility evaluation. These parameters are exactly opposite for writing, giving it a low utility evaluation. In the end, though socializing’s Integrating Theories of Motivation 27 positive component is still temporally unchanged, its negative component is more temporally proximate, diminishing its utility. Similarly, the negative component for writing is still experienced immediately, but now its positive component is also relatively imminent, thus increasing its utility. Writing activity eventually becomes increasingly likely as the deadline approaches, occurring in this example on December 5 for Jess, but six days earlier for Jane, on November 29. APPLICATIONS OF TMT George Akerloff, the Nobel Prize winning economist, proposed that his field should take salience into account (1991). Salience refers to individuals being unduly sensitive to the present and consequently undervaluing the future. He shows that the concept has broad ramifications on topics as diverse as retirement savings, organizational failures, cults, crime, and politics. Temporal Motivational Theory has an analogous concept of delay sensitivity, and thus also has the potential to shape the discussion in several areas. Here we review four topics that have already incorporated elements of TMT, especially the more novel concept of hyperbolic discounting: consumer behavior, aggression, stock market behavior, and governmental behavior. As a general theory of human motivation, other applications are plentiful though. For further examples see Thaler (1991), who also considers many other ramifications of prospect theory and temporal discounting, both fundamental components of TMT. Also, addictive behaviors in particular have been examined from several perspectives very similar to TMT (Glasner, in press; Petry, 2001; Rachlin, 2000). Consumer Behavior There has already been a fair amount of TMT-type research on consumer behavior. Saving behavior, rebates, suggested retail prices, and impulse purchases have all been discussed Integrating Theories of Motivation 28 using prospect theory and some forms of temporal discounting (Baumeister, 2002; Thaler, 1991). Aspects of TMT can also be found throughout the sales process. For example, one selling strategy is to emphasize what the prospect might be losing if he or she does not buy, given that sales folklore states, “the fear of loss is often greater than the desire for gain” (Ziglar, 1991: 188) or that “trouble always takes precedence over growth” (Miller, Heiman, & Tuleja, 1985: 123). This tip is evidently an independently derived version of Kahneman and Tversky’s (1979) “losses loom larger than gains.” Alternatively, a popular strategy to induce a sale is to emphasize that “if the decision is yes, then you...could be enjoying the benefits NOW!” (Ziglar, 1991: 253). This is very similar to allowing people to “buy-now, paylater,” often the harbinger of excessive credit-card debt. These methods appear to exploit the discounting function, given that benefits of the purchase are experienced immediately while the impact of the cost is significantly delayed. Going beyond explanation, it is apparent that TMT can predict market behavior. Recently, economists have noticed a tremendous difference in bidding behavior between the two Internet auctioneers, Amazon.com and eBay (Roth & Ockenfels, 2002). Both stipulate a deadline for their auctions but Amazon.com always grants a ten-minute continuance from its last bid while eBay keeps its final time firm. As the discounting functioning predicts, it is primarily eBay’s customers who engage in a crush of last-minute bidding. Finally, there have been some preliminary studies that assess how TMT parameters might differ among various market segments. For example, Thaler (1991) summarizes research indicating that African-Americans discount more than Caucasians, though the conclusion’s validity has been challenged (Banks, McQuater, Anthony, & Ward, 1992). Also, the younger 11 It should be noted that impulsivity differences among ethnic groups is likely to become an extremely controversial issue, having a potential similar to the storm cloud that hangs over the issue of race and intelligence. At present, Banks et al.’s (1992: 341) review of this topic already appears to reflect an emotional charge as they indicate “experimental data largely represent Blacks either as preferring delayed gratification or as indifferent toward Integrating Theories of Motivation 29 and the poorer tend to discount more than the older and the wealthier (Green, Myerson, Lichtman, Rosen, & Fry, 1996; Holden, Shiferaw, & Wik, 1998; Nielsen, 2001). Unfortunately, there is little other research to cite. Other individual variables have been almost completely neglected, curiously characterized as irrelevant to the study of consumer behavior, thus most researchers have yet to explore this avenue of research (Albanese, 1990; Engle & Blackwell, 1995; Tybout & Artz, 1994). Aggression As the review of workplace violence by Glomb, Steel, and Arvey (2002) confirms, aggressive behavior can be largely understood in the TMT terms of value and discounting, specifically as the interplay of trait anger and trait impulsiveness. Those who have elevated states of anger combined with impulsiveness are the most likely to become violent. The role of impulsiveness is considered so important in the expression of violence that Gottfredson and Hirschi (1990) argue that most criminality reflects just this one aspect. It is not surprising, then, that Berkowitz (1997) decomposes violence into a formulation that he himself considers very similar to that of Dollard and Miller (1950), and thus to TMT. For example, Berkowitz (1997: 202) discusses how the certainty as well as the severity of punishment affects its inhibitory effects on aggression. He also relates violence to the discounting function in that, “the strength of the tendency to perform a goal-oriented response (in this case, to inflict an injury) and to avoid performing the action (that is, to inhibit one’s aggression because of the possibility of punishment) increased the closer the organism came to the goal.” Stock Market immediate versus delayed rewards.” This is almost certainly an overstatement, putting African-Americans as a farfetched exception to the basic psychological phenomenon of temporal discounting. The question is not whether we discount, which is well established and often adaptive, but to what degree. Integrating Theories of Motivation 30 It has long been noted that the behavior of stock markets does not appear to be entirely rational. Schiller (2000) touches on several instances of this such as the British South Sea Bubble of 1720 or the Japanese real estate bubble of the late 1980s. More recent in 1996, the Dow Jones reflected what Federal Reserve Board Chairperson Alan Greenspan suggested as displaying “irrational exuberance.” Economists have, for the most part, concluded that investors do tend to be risk averse, in accordance with Prospect Theory and thus TMT. However, it appears that the stock market is also vulnerable to temporal discounting. In a series of papers, De Bondt and Thaler (see Thaler, 1991) review research demonstrating that the stock market as well as stock market analysts overreact to unexpected and dramatic news events, both that is favorable and disagreeable in nature. Specifically, “investors seem to attach disproportionate importance to short-run economic developments” (Thaler, 1991: 259). Though De Bondt and Thaler interpret this effect primarily as an instance of Kahneman and Tversky’s (1979) representative heuristic, from a TMT perspective it also appears to be an excellent indication of temporal discounting. Consider the effect of bad news. Unlike anticipated problems, sudden and surprising news of misfortune suggests an impending downturn in the stock price. The company value will diminish and consequently so will the value of the stock. Some selling is, of course, then rational and a dip in price is to be expected. However, stockholders with a high discount function will overvalue this imminent loss and will oversell to minimize it. The stock price will plunge past the optimal point to where it actually becomes more rational to buy given its expected long-term performance. This overreaction is formally exploited in the investment technique called “Dogs of the Dow” (O’ Higgins, 1991). Also, stock repurchasing programs seem to be an explicit attempt to manage such shareholder shortsightedness (Sanders & Carpenter, 2003). Integrating Theories of Motivation 31 Governmental Behavior In an intriguing chapter, Elster (1992) examines how temporal discounting is implicitly anticipated and counteracted in many political institutions. He states, “In the heat of passion or under the influence of some immediate temptation, an individual can deviate from prudent plans formed in advance or do things he will later regret. Groups of individuals, such as voters or members of a political assembly, are no less prone to such irrational behavior” (Elster, 1992: 3940). To deal with this inherent weakness, constitutions are often drawn that enact forms of precommitment. Part of this precommitment is limiting rules that we bind ourselves to so as to avoid later regrettable actions. Another precommitment is a bicameral system, where decisionmaking must pass through two chambers representing the electorate, such as a Congress and a Senate (Joint Committee on the Organization of Congress, 2003). Retelling the “saucer anecdote” of George Washington helps to illustrate the wisdom of this builtin delaying mechanism. In a conversation between Thomas Jefferson and Washington, Jefferson asked why a senate should be established. “Why,” Washington responded, “do you pour coffee into your saucer?” “To cool it,” Jefferson replied. “Even so,” Washington said. “We pour legislation into the Senatorial saucer to cool it” (Farrand, 1966: 359). Other countries offer similar explanations. In Canada, the Senate is often referred to as “the house of sober second thought.” Supplementing this political analysis is the issue of the central bank. Using the term “dynamic inconsistency,” it is observed that central banks are tempted at times to increase the money supply and thus cause inflation merely to immediately reduce unemployment (for a review, see White, 1999). An unconstrained central bank may excessively exploit this option, to the detriment of the country’s long-term economic health. Haubrich (2000) discusses the use of policy rules and removing the central bank’s discretion to counteract this trend. The policy rules Integrating Theories of Motivation 32 are interpreted as a form of pre-commitment, similar to “Ulysses lashing himself to the mast....as both [government and central banks] face temptations to act at a given moment in ways that run counter to their long-range goals” (Haubrich, 2000: 1). FUTURE RESEARCH Temporal Motivational Theory does appear to account for a wide-range of human behavior. Despite this breadth, its components are falsifiable, and considerable work has already been done to validate it. Its expectancy and value components have already been well assessed by many researchers, more recently by Tversky and Kahneman (1992). Its discounting function is the culmination of extensive and varied investigations, as summarized by Ainslie (1992). Needs themselves have been studied for the better part of a century (e.g., Murray, 1938; Winter et al., 1998). Still, a few steps remain. As mentioned, TMT can be integrated with other motivational and decisional theories, improving its consilience, and this should be done. In addition, some further refinements should be confirmed or considered. The hypothesis that there are separate discounting terms for positive and negative events can be more effectively demonstrated. Also, though the motivational system appears to be well represented by an approach and avoidance duality, a trichotomy may be the more appropriate model. Finally, we suggest two promising venues for conducting future research. Impulsiveness: Positive and Negative Drawing on research from both economics and psychology, we conclude that the temporal discounting function is different for both positive and negative events, a position consistent with the considerable research that our motivational systems for gains and losses are somewhat independent. However, these are inferential findings and the field research done on Integrating Theories of Motivation 33 the analogous construct of impulsiveness has yet to come to an identical conclusion. Instead, a myriad of other theoretical proposals exist, decomposing the construct into up to eight facets. For example, in a review of impulsiveness (Evenden, 1999), only Cloinger’s (1987) tridimensional formulation comes close to offering a similar description. Cloinger does conclude there are separate impulsiveness systems for gains (i.e., novelty seeking) and for losses (i.e., harm avoidance), but also suggests a third system called persistence. This three-factor solution has received recent support (Torrubia, Ávila, Moltó, & Caseras, 2001; Whiteside & Lynam, 2001), though more work should be conducted. To concisely demonstrate that there is at least positive and negative impulsiveness would not only buttress the fundamental structure of TMT, but also would be a major advance by furthering our basic understanding of impulsiveness itself. As it is presently conceived, it has uncertain qualities, sometimes associated with extraversion, other times with neuroticism, and often with conscientiousness (Revelle, 1997). Two or Three Factors The structure of TMT is based on the notion that the mind can be parsed into an approach and avoidance motivational system. However, as the previous work on impulsiveness initially suggests, further decomposition may be considered. Specifically, the avoidance or negative side of our nature appears to be less than unitary. For expectancy related research, optimism appears to be better understood as three factors: optimism, pessimism and “fighting spirit” (Olason & Roger, 2001). Similarly, people’s coping styles for uncertainty yield three similar factors (Greco & Roger, 2001): emotional uncertainty (avoidance); desire for change (approach); and cognitive uncertainty (persistence). From a broader perspective, Raghunathan and Pham (1999) noted substantive differences between the influences of sadness and anxiety on decision making. Similarly, Krueger (1999), in Integrating Theories of Motivation 34 an examination of mental disorders, found a three-factor model explained comorbidity. Specifically, fear and anxiety-misery were best understood as two sub-factors of a high-order internalizing factor. Finally, recent neuropsychological reviews do indicate the presence of other systems (Gray & McNaughton, 1996; Lang, Bradley, & Cuthbert, 1997; Rothbart, Ahadi, & Evans, 2000), such as fight-orflight. Also, different brain functions tend to employ separate as well as common mechanisms, making truly orthogonal factors an inevitable fiction. It is clear then that the approach/avoidance model is a simplification, but this does not necessary indicate the need for immediate revision. It remains to be seen whether the precision gained by adding other elements will be worth the cost in parsimony. Research Venues The majority of previous work on TMT concepts, especially temporal discounting, relied on comparative psychology (i.e., animal research) and “casino” situations where expectancy and value are expressed explicitly, typically in terms of ratios, dollars, and deaths. These situations give a great deal of control, but their limited realism makes their generalizability suspect (Bazerman, 2001). Consequently, there has been a movement towards Naturalistic Decision Making research (Kühberger, Schulte-Mecklenbeck, & Perner, 2002). Ideally, we would like to test further refinements to TMT on a wide-range of people who are striving at their own pace towards an important goal in a standardized but realistic setting in which we can precisely but easily measure their behavior. Though this is a long list of specifications, there is at least one venue that provides all these features, a computerized personal system of instruction (C-PSI). Though personal system of instructions or programmed learning has been in use for decades, a computerized version has several desired qualities. As used by Steel, Brothen, and Wambach (2001), hundreds of students simultaneously work towards completing a University course at Integrating Theories of Motivation 35 their own pace, allowing choice and thus motivated behavior. Furthermore, progress is assessed at an unparalleled number of points as the course is broken down into numerous assignments (e.g., 78), all computer administered with completion precisely recorded. Similarly, a host of other observed and selfreport measures can be easily inserted into this framework. The only restriction is that students must finish these assignments by the final exam. Consequently, the efficacy of selfregulatory interventions based on the TMT model can be clearly evaluated. We can see not only the outcome, but can examine in detail people’s progression towards their goals. Another novel venue for TMT research is the construction of simulations. Recent advances in parallel computing are allowing us to effectively model extremely complex phenomena, such as global weather patterns (Clauer et al., 2000) or applied nuclear physics (Bigelow, Moloney, Philpott, & Rothberg, 1995). Consequently, this technology is also being applied to recondite areas of human decision-making, such as traffic (Pursula, 1999) and market behavior (Janssen & Jager, 2001), as well as several organizational science topics (Hulin, Miner, & Seitz, 2002). Unfortunately, the use of computational modeling has been hindered by the lack of psychological theory to aid in their construction (Sauer, Wastell, & Hockey, 2000). If consensus indicates that TMT does indeed provide a good approximation of decision-making, it provides the foundation for a new generation of simulators that can be used to initially test a wide variety of motivational interventions, such as compensation systems or job design. Already, a rudimentary model incorporating the notion of needs, satiation, and temporal discounting exists. It is the “The Sims,” the most popular computer game of all time, based on the principles of consumer and evolutionary psychology (Johnson, 2002; Pearce, 2002). CONCLUSION 12 For an interesting application, see the political economist Heath (2001), who used the Sims to simulate the effects of lifestyle choices on work-family conflict. Integrating Theories of Motivation 36 Though we have benefited by exploring human nature from many different perspectives, we would also gain by considering and consolidating commonalities. For example, the extremely well-supported time-discounting function evident in behaviorist and economic understanding of human nature is largely overlooked in other areas. In fact, most motivational reviews fail to refer to it (e.g., Franken, 1994; Kanfer, 1990; Kleinbeck, Quast, Thierry, Häcker, 1990; Mitchell, 1997). On the other hand, economists have maintained since at least Stigler and Becker (1977) that tastes or preferences, that is needs or traits, provide little or no prediction or explanation of human behavior. During the 1970s, this was a plausible and popular position, even within psychology (e.g., Mischel, 1973). However, as Caplan (2003) outlines, our empirical findings over the last quarter century indicate that it is increasingly outlandish to maintain such a belief. Temporal Motivational Theory addresses such dysfunctional separation by unifying insights from several different theories of motivation. Importantly, this is not a definitive model accounting for every aspects of human behavior, but it does provide a common framework of essential features. Using it, the extensive contributions from individual disciplines may be better shared by all, such as cognitive psychology determining how expectancies change with experience or the findings from the self-regulatory disciplines indicating how impulsiveness may be tempered. As Barrick and Mount (1991: 23) concluded, “...in order for any field of science to advance, it is necessary to have an accepted classification scheme for accumulating and categorizing empirical findings.” This model can provide common ground to enable the necessary dialogue. Integrating Theories of Motivation 37 REFERENCESAinslie, G. 1992. 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