Psychology of Aesthetics, Creativity, and the Arts 2011, Vol. 5, No. 1, 3–12
© 2011 American Psychological Association 1931-3896/11/$12.00 DOI: 10.1037/a0017698
Rational Versus Intuitive Problem Solving: How Thinking “Off the Beaten Path” Can Stimulate Creativity Erik Dane
Markus Baer
Rice University
Washington University in St. Louis
Michael G. Pratt
Greg R. Oldham
Boston College
Tulane University
We compared the effects of rational versus intuitive problem solving on creativity. We argued that the relative effectiveness of these approaches depends upon an individual’s typical thinking style such that individuals will be more creative when they adopt a problem-solving approach that differs from their typical style of thinking (e.g., individuals who avoid rational thinking will exhibit higher creativity when they are instructed to rely on rational problem solving). We tested this hypothesis in a sample of undergraduate students generating creative ideas in response to a real-world problem. In support of our hypothesis, we found that problem-solving approach and individual differences in thinking style interact such that creativity is highest when individuals use a nontypical problem-solving approach. Keywords: creativity, rational versus intuitive problem solving, thinking style
Considerable evidence suggests that creativity is essential to such critical goals as fostering innovation in organizations, achieving scientific breakthroughs, and developing high-quality educational systems (e.g., Amabile, 1996; Craft, Jeffrey, & Leibling, 2001; Csikszentmihalyi, 1996). Perhaps because of this growing recognition of the merits of creativity across a variety of contexts and domains, scholars have posited various techniques for developing creative solutions for challenging problems. Within this line of inquiry, some have suggested there are distinct approaches that individuals may adopt with the aim of achieving creative solutions. For example, when individuals focus on a particular facet of creativity (e.g., originality, flexibility) as they develop ideas, this targeted facet of creativity may be enhanced (e.g., Runco & Okuda, 1991). Likewise, when individuals draw upon particular tactics (Runco, Illies, & Reiter-Palmon, 2005) or heuristics, such as analogical and case-based reasoning (Scott, Lonergan, & Mumford, 2005), which provide procedural information about how to develop creative ideas, higher levels of creativity may ensue. More broadly, a number of problem-solving approaches have been advocated to stimulate the generation of creative ideas (e.g., Parnes, 1987; VanGundy, 1988). Couger (1995) classified various creativity techniques by distinguishing rational from intuitive approaches. The former approaches are designed to produce creativity through system-
atic, deliberative patterns of thought; the latter approaches are intended to spur creativity through gestalt-like, holistic cognitive associations. Scholars have reached different conclusions regarding which, if either, of these problem-solving approaches is more conducive to creativity (e.g., Garfield, Taylor, Dennis, & Satzinger, 2001; Kaufmann & Vosburg, 1997; Weisberg, 1986). The study reported here attempts to better understand the effects of rational and intuitive problem-solving approaches on creativity— or the production of novel and potentially useful ideas (Amabile, 1996; Oldham & Cummings, 1996; Shalley, Zhou, & Oldham, 2004). Recognizing that extant research along these lines is limited and, in some cases, at odds, we seek to build upon and reconcile different perspectives on this topic by considering the possibility that not all individuals will benefit in a similar manner from a rational versus intuitive problemsolving approach. In particular, we draw on the observation that differences in individuals’ natural or typical ways of thinking may lead people to respond differentially to certain problemsolving methods (O’Hara & Sternberg, 2001; Puccio, Wheeler, & Cassandro, 2004). Research suggests that there are systematic differences among individuals with respect to their tendency to employ rational versus intuitive thinking (Epstein, Pacini, Denes-Raj, & Heier, 1996; Pacini & Epstein, 1999), and we suggest that these differences may moderate the effects of rational versus intuitive problem-solving approaches on creativity. Specifically, we investigate whether creativity is fostered when individuals are instructed to adopt a “nontypical” approach to solving problems—an approach that differs from their typical style of thinking. This is in line with previous research calling for work examining whether the type of problem-solving approach being advocated should reinforce or complement an individual’s typical thinking style (Garfield et al., 2001; Huber, 1983).
Erik Dane, Jesse H. Jones Graduate School of Business, Rice University; Markus Baer, Olin Business School, Washington University in St. Louis; Michael G. Pratt, Carroll School of Management, Boston College; Greg R. Oldham, A. B. Freeman School of Business, Tulane University. Correspondence concerning this article should be addressed to Greg R. Oldham, A. B. Freeman School of Business, Tulane University 7 McAlister Drive, New Orleans, LA 70118. E-mail:
[email protected] 3
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By focusing on two types of problem-solving approaches— rational versus intuitive—we are drawing on an expanding line of research positing the existence of two distinct, relatively independent, systems of information processing within human beings (Epstein, 2002; Sloman, 1996). One system of information processing enables individuals to learn information deliberately and engage in analyses in an attentive manner (Bargh & Chartrand, 1999; Kahneman, 2003; Stanovich & West, 2000). Following the work of Epstein (1994, 2002), we refer to this system as rational. When an individual approaches a problem systematically and deliberately, a rational thinking mode is being employed. Rational thinking generally occurs in a linear or sequential manner, as opposed to through holistic or associative connections—processes that characterize the second processing system. This second system involves the automatic and relatively effortless processing of information (Bargh & Chartrand, 1999; Kahneman, 2003; Stanovich & West, 2000). The cognitive operations (though not necessarily the products) of this system tend to be inaccessible to consciousness (Dane & Pratt, 2007). Again following the work of Epstein (1994, 2002), we refer to this system as experiential. Numerous scholars have argued that intuitions arise through the experiential system of information processing (e.g., Barnard, 1938; Hogarth, 2001; Shapiro & Spence, 1997). As such, intuitions are posited to be nonconscious, rapid, affectively charged, and holistic (Dane & Pratt, 2007). Although the mental steps precipitating intuitions generally cannot be logically grasped (because of their nonconscious origins), their outcomes, intuitive judgments, represent the conscious manifestations of experiential processing. In summary, the rational and experiential systems of processing are relatively independent ways of thinking that individuals may draw upon to greater or lesser extents in approaching various tasks. Below, we examine two problem-solving approaches—rational and intuitive—which correspond to the rational and experiential systems, respectively.
proaches may be effective in fostering creative ideas (e.g., Couger, 1995; Kaufmann & Vosburg, 1997; Weisberg, 1986). The generation of new ideas or solutions is often portrayed as a process involving a series of steps. Confronted with a problem, individuals go through a preparation stage in which they access relevant information and potential response algorithms allowing them to generate potential solutions which are then evaluated and refined until the problem is solved or has been adequately addressed (Amabile, 1996). Because rational approaches permit individuals to proceed in a logical, sequential fashion (see Janis & Mann, 1977), rational problem solving may enable individuals to effectively address the various steps that some researchers associate with idea generation. Other scholars maintain that creativity may be enhanced by intuitive approaches. For example, it has been suggested that intuitive problem solving may play a fundamental role in fostering creative ideas because of its holistic and associative cognitive features (Dane & Pratt, 2007). Such associative processing may foster divergent thinking, which is commonly viewed as accounting for the production of creative ideas (see Barron & Harrington, 1981). Along similar lines, Miller and Ireland (2005) have suggested that intuitive thinking may produce “holistic hunches,” which, if heeded, may spur the development of novel business products or practices. Empirical support for a link between intuitive problem solving and creativity is provided by Garfield and colleagues (2001), who found a positive relation between the use of an intuitive creativity technique and the generation of ideas that ranked high in novelty. Given these various arguments and findings, it is not clear whether the use of a rational or intuitive problem-solving approach is better suited to the production of creative ideas. To address this lack of convergence in the literature, we suggest that previous research has largely neglected the effect of a potentially critical moderating factor—individual differences in thinking style. Below, we discuss whether and how problem-solving approach and individual differences in thinking style operate in tandem to jointly influence creativity.
Rational Versus Intuitive Problem-Solving Approaches and Creativity
Interaction Between Problem-Solving Approach and Thinking Style Differences
Drawing on the problem-solving literature (Couger, 1995; VanGundy, 1998) and the dual process view of information processing reviewed earlier (e.g., Epstein, 2002; Kahneman, 2003; Sloman, 1996), we differentiate between rational and intuitive problemsolving approaches. Rational problem solving involves using a structure to produce a logical, linear pattern of thought. Rational problem solving occurs through adopting elements often associated with the prototypical rational decision-making model. For example, individuals may develop task-specific criteria in advance and attempt to generate ideas in line with these criteria. Intuitive problem solving occurs when individuals give credence to their “gut” judgments and do not attempt to systematically and analytically solve a problem, such as by developing and applying taskspecific criteria (see Couger, 1995 and Garfield et al., 2001, for more on the nature of rational and intuitive problem-solving approaches). Research connecting problem-solving approaches to creativity is limited. Some scholars argue that rational problem-solving ap-
Recent research suggests that there are relatively stable differences across individuals in the extent to which they typically engage in a certain kind of thinking when approaching problems (e.g., Allinson & Hayes, 1996; Pacini & Epstein, 1999). To describe these individual differences in thinking style, a number of different taxonomies have been suggested, some of which have been examined with respect to creativity (e.g., Clegg, Unsworth, Epitropaki, & Parker, 2002; Guastello, Shissler, Driscoll, & Hyde, 1998; Meneely & Portillo, 2005; O’Hara & Sternberg, 2001). In the present study, we focus on a framework that closely parallels the distinction we drew between rational and intuitive problemsolving approaches. According to Epstein and colleagues, individuals vary in the degree to which they naturally tend to rely on rational versus intuitive thinking when engaging in problem solving and decision making (Epstein et al., 1996; Pacini & Epstein, 1999). Their work demonstrates that some individuals prefer to solve problems in a rigorous, analytical manner, whereas others shirk from engaging in such thinking. Likewise, some individuals
Two Systems of Information Processing
SPECIAL ISSUE: RATIONAL VERSUS INTUITIVE PROBLEM SOLVING
prefer to use their intuitions when solving problems, while others question their utility and, thus, eschew their intuitive judgments. Although individuals do have propensities to use certain types of thinking, research suggests that the approach individuals’ actually use to solve a problem may also be influenced by various internal and external conditions. For example, research indicates that moods may trigger the use of certain decision styles (e.g., Elsbach & Barr, 1999; Isen, Means, Patrick, & Nowicki, 1982). In addition, Dane and Pratt’s (2007) review suggests a variety of conditions that may make the use of intuition more likely; these conditions range from individual circadian variations to cultural values, such as low uncertainty avoidance. More central to the present study, researchers have shown that individuals may be directly instructed to adopt a particular problem-solving approach (e.g., Garfield et al., 2001). Research in this area indicates that giving individuals a specific problemsolving approach may interact with their preferred thinking styles (Puccio et al., 2004; Sternberg & Grigorenko, 1997). For example, Puccio et al. (2004) found that individuals with certain thinking styles (e.g., divergent thinking) were more likely to enjoy a course on developing creative thinking skills. Similarly, examining the effects on creativity of different instructions (to be analytical, practical, or creative), O’Hara and Sternberg (2001) showed that thinking style preferences determined the creativity of individuals working under different instructions. To illustrate, instructions to be practical led to more creativity among those who preferred to play with their own ideas (i.e., those with a legislative style) than among those who preferred to analyze and evaluate their ideas (i.e., those with a judicial thinking style). Although these studies have not explicitly examined differences in rational versus intuitive thinking, this research nevertheless highlights the importance of considering individual differences in thinking style when exploring the effectiveness of problem-solving approaches in stimulating creativity. By extrapolation, it is reasonable to assume that problemsolving approach and thinking style may operate in tandem to jointly influence creativity. However, perhaps the more important question is how they combine to affect creativity. Specifically, as suggested by Huber (1983), it is not clear whether the required problem-solving approach should reinforce an individual’s thinking style (e.g., those with a rational style should be required to employ a rational problem-solving approach) or complement it (e.g., those with rational style should be required to employ an intuitive problem-solving approach). Previous research on creativity provides some clues as to how both factors may combine to shape the generation of new, potentially useful ideas. Specifically, some researchers have argued that creativity may be enhanced when individuals explore novel cognitive pathways (Amabile, 1996; Newell, Shaw, & Simon, 1962). Individuals who find themselves in a situation in which nonstandard cognitive pathways are called upon may interpret their problem environment as unusual and, thus, conducive to novel associations, thereby triggering set-breaking cognitive associations that ultimately result in elevated levels of creativity (Newell et al., 1962). In support of this logic, a number of creativity training techniques, such as DeBono’s (1985) “Six Thinking Hats,” are based on the premise that creativity is boosted when people venture into unchartered territories and engage in ways of thinking they typically fail to employ. Likewise, Couger (1995, p. 42)
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argued that an effective creative problem-solving approach is one designed to “force persons to move out of their normal problem solving mode.” These arguments suggest that creativity may be enhanced when problem-solving requirements differ from an individual’s natural thinking style. In line with this logic, we hypothesize that individuals’ typical thinking styles will interact with problem-solving approach to affect creativity such that individuals will be more creative when using a problem-solving approach that differs from their natural thinking style tendencies. This interaction perspective, if supported, would imply that neither rational nor intuitive problem-solving approaches are necessarily more conducive to creativity, but rather that problem-solving approaches and thinking style tendencies must be considered in combination to comprehensively understand how different problem-solving approaches relate to creativity.
Method Participants We tested our hypothesis in a laboratory experiment. Our experimental task was based on an actual problem that a local organization, an international gift store, was experiencing. Specifically, two senior managers at this store, who also later served as our raters of the generated ideas (see below), informed us about their problem of being unable to attract a sufficient number of student visitors to the store. Thus, although the participants in our study were students, the task they were assigned was of a realworld nature, and their responses to the task were evaluated by actual managers. Participants were recruited for this experiment from three undergraduate business courses at a large Midwestern university. The sample consisted of 59% women and 56% Caucasians. The average age of our sample was 20.60 years (SD ⫽ 1.32). Students were granted extra credit points for their participation. A total of 180 students participated. Of these, 179 provided complete information. The number of participants who attended the experimental sessions ranged from 15 to 20.
Procedures and Task Prior to performing the experimental task, participants completed the Rational-Experiential Inventory (REI; Pacini & Epstein, 1999) at their computer workstation using an online data collection program. The experimenter then explained that the study involved generating ideas and instructed participants to open a Web site that provided a description of the gift store noted above and the current problem that it faced—increasing the number of student visitors to the store. Participants were instructed to generate as many original and practical suggestions as possible regarding how to attract students to the store. They were offered a $10 gift certificate to the store for each idea they generated that the store managers ultimately adopted. Depending on the problem-solving condition to which they were assigned (see below), participants were instructed to generate their ideas using either an intuitive or a rational problem-solving approach. They were given 10 min to generate ideas by typing them at their computer workstation. At the conclusion of this task, participants completed a brief questionnaire
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that included manipulation check items and measures of the control variables. After completing this questionnaire, participants were debriefed and dismissed.
Manipulation of Problem-Solving Approaches Participants were randomly assigned to one of two problemsolving conditions: intuitive or rational. The manipulation of these problem-solving approaches was adapted from procedures used in previous studies to induce intuitive (Dane, Rockmann, & Pratt, 2009; Jordan, Whitfield, & Zeigler-Hill, 2007) and rational thinking (McMackin & Slovic, 2000; Wilson & Schooler, 1991). As detailed below, each condition involved the use of explicit instructions intended to foster a particular approach to problem solving. The instructions employed in our study were not directed toward cultivating certain types of creativity, but rather were intended to convey to participants how they should go about generating creative ideas (i.e., either intuitively or rationally). As such, the instructions we used were similar to certain creative problemsolving tactics and heuristics that have been examined in other studies (e.g., Runco et al., 2005; Scott et al., 2005), which are likewise designed to provide specific operations or strategies for creative idea generation. Intuitive problem-solving approach. Participants were told that they would be performing a task that involved the generation of ideas. They were then given specific instructions to generate their ideas based on their “intuition, or first impression.” They were instructed to avoid thinking very hard about what the “right” idea is and, instead, to generate ideas based on their “gut instinct” reactions. Following this manipulation, participants were then given the task of generating original and practical ideas designed to increase student visitors to the store. Immediately prior to beginning the task, participants were again given the instruction: “Be sure to rely on your “gut instinct” reactions when generating your ideas.” Rational problem-solving approach. Participants were given the following instructions prior to learning the specific nature of the task: “Based on your own experience, as well as what you may have learned in your business classes, think about the factors that individuals in organizations should consider when generating creative ideas. Please list these factors on the sheet in front of you.” Participants were given 2 min to list relevant factors on a sheet of paper. They were then told that on the task they were about to complete they should consider the list of factors they had developed and ignore any first impressions or “gut instincts.” They were told to be as analytical as possible when generating ideas. Following this manipulation, participants in this condition were then given the task of generating original and practical ideas designed to increase the number of student visitors to the store. Immediately prior to beginning the task, participants were again given the instruction: “Be sure to be as analytical as possible when generating your ideas.”
Measures Creativity. To measure creativity, we employed the following two-step procedure. In the first step, the first and second authors jointly reviewed a random subset of 10% of all 1398 ideas that had been generated by participants with the goal of establish-
ing a classification system by which the majority of ideas—many of which appeared numerous times in the overall idea set and were therefore redundant— could be categorized. This was done to reduce the number of ideas that had to be reviewed by the two store managers who agreed to serve as our raters. After establishing a preliminary set of categories, both authors jointly reviewed the remaining 90% of ideas sorting them into the initially derived categories while at the same time modifying and refining the classification system. This process resulted in a set of 22 categories (i.e., “offer discounts/coupons” and “sponsor events on campus”). A total of 1110 (approximately 79%) ideas fell into one of the 22 categories, leaving 288 ideas uncategorized. In the second step, we asked the two store managers to rate the 22 categories and the remaining noncategorized ideas. We provided a number of illustrative examples for each category and, in order to cue the raters regarding the originality of each idea, we indicated for each category the number of ideas that fell into the category. Managers rated these categorized ideas, as well as the remaining noncategorized ideas, on a scale that ranged from 1 (not at all creative) to 9 (extremely creative) using the following definition of creativity: “Creative ideas are both original and potentially useful. In other words, they are judged as novel and practical for the organization.” To examine interrater reliability, we calculated the intraclass correlation coefficient which is equivalent to Cronbach’s alpha (Shrout & Fleiss, 1979). The coefficient was .97 for the 22 categories and .90 for the noncategorized ideas, indicating that the managers were generally consistent in their ratings. Thus, we averaged the ratings across the two raters. To obtain a creativity score for each idea rather than each category of ideas, we assigned all ideas in a category the average creativity score assigned by the two raters to the category. For example, all ideas in the category “offer discounts/coupons” received a creativity score of 4 —the average score assigned to this category by both raters. Using these scores, we calculated two indicators of creativity for each participant. First, we summed the creativity scores across all ideas generated by each participant and then divided the sum by the total number of ideas to derive an indicator of average creativity. However, because idea generation tasks, such as the one employed in this research, are expected to result in the production of ideas that are truly novel and have the potential to be implemented (e.g., Diehl & Stroebe, 1987), we developed a second indicator of creativity reflecting the extent to which participants produced ideas that were rated as above average in creativity. Similar to previous research (Goncalo & Staw, 2006), we counted the number of ideas that received a higher than average creativity rating and then divided this number by the total number of ideas produced by each participant. The resulting variable indicated the percentage of ideas that were rated as above average in creativity for each participant. Typical thinking style. We measured individuals’ typical thinking styles via the REI (Pacini & Epstein, 1999). Participants completed the entire inventory, which included a 10-item measure of experiential engagement and a 10-item measure of rational engagement. Participants responded to each item on a scale that ranged from 1 (definitely not true of myself) to 5 (definitely true of myself). Confirmatory factor analyses revealed that a two-factor solution fit the data sufficiently well (2169 ⫽ 319.13, p ⬍ .01, adjusted goodness-of-fit index (AGFI) ⫽ .82, comparative fit
SPECIAL ISSUE: RATIONAL VERSUS INTUITIVE PROBLEM SOLVING
index (CFI) ⫽ .86, root mean square error of approximation (RMSEA) ⫽ .07) and significantly better (⌬21 ⫽ 335.28, p ⬍ .01) than a one-factor solution (2170 ⫽ 654.41, p ⬍ .01, AGFI ⫽ .54, CFI ⫽ .54, RMSEA ⫽ .13). Consequently, we averaged the 10 items for each measure to form two indices. The Cronbach’s alphas for experiential and rational engagement were .86 and .81, respectively. Control variables. Because research suggests that women may be more creative on some tasks than men (Amabile, 1996), we included gender (0 ⫽ male; 1 ⫽ female) in our analyses. In addition, because domain experience may relate to creativity (e.g., Ericsson, 1999; Mumford & Gustafson, 1988; Weisberg, 1999), we controlled for whether participants had completed a marketing internship (0 ⫽ no; 1 ⫽ yes).
Manipulation Check To evaluate the degree to which participants complied with our problem-solving approach manipulations, each participant responded to five items adapted from Dane et al. (2009) in which response options ranged from 1 (strongly disagree) to 7 (strongly agree): I based my ideas on my inner feelings and reactions; I generated ideas in a logical and systematic way (reverse scored); I relied on my gut instinct; I analyzed all available information in detail (reverse scored); I used ideas that felt right to me. Responses to these items were averaged to form an index (Cronbach’s alpha ⫽ .71).
Results Manipulation Check Univariate analysis of variance for the manipulation check index revealed a significant main effect for problem-solving approach, F(1, 177) ⫽ 41.59, p ⬍ .01. Consistent with our manipulation, participants in the intuitive problem-solving condition reported engaging in significantly more intuitive thinking when generating ideas than participants in the rational problem solving condition (M ⫽ 4.81 vs. M ⫽ 3.99). Next, to examine the possibility that interactions between problem-solving approach and the experiential and rational engagement measures might contribute to the manipulation check index, we conducted moderated regression analyses. Dummy codes were used to represent problem-solving approach (0 ⫽ intuitive problem solving; 1 ⫽ rational problem
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solving). After centering the engagement measures (Aiken & West, 1991), we regressed the manipulation check measure on the main effect variables (experiential engagement, rational engagement, and problem-solving approach) and the two interaction terms (experiential engagement ⫻ problem-solving approach and rational engagement ⫻ problem-solving approach). Results showed that the interactions were statistically nonsignificant (s ⫽ .04 & .09, ps ⬎ .05). Based on these results, we concluded that our manipulations were successful.
Preliminary Analysis As shown in Table 1, gender was positively related to average creativity but not above average creativity, indicating that women generated ideas rated on average as significantly more creative than those produced by men (r ⫽ .20, p ⬍ .01). Consistent with previous research (Pacini & Epstein, 1999), we found women to score higher on experiential engagement than men (r ⫽ .15, p ⬍ .05). Rational and experiential engagement were only moderately correlated (r ⫽ .18, p ⬍ .05), supporting claims that these factors are tied to separate processing systems (Pacini & Epstein, 1999).
Hypothesis Test To test our hypothesis, we conducted moderated regression analyses. For each regression model, we analyzed the residuals to verify that the standard assumptions of regression analysis were met (Hair, Anderson, Tatham, & Black, 1998). These analyses revealed that the error terms maintained a consistent variance and were normally distributed (as determined by a normal probability plot). Inspection of the variance inflation factors for each regression model revealed that multicollinearity was not a concern in this study (all variance inflation factors were less than 3). Hence, our regression models met the standard assumptions of regression analysis. Table 2 presents the results of the regression analyses. In these analyses, we regressed both creativity measures on the control variables (i.e., gender and marketing internship), the main effect terms (experiential engagement, rational engagement, and problem-solving approach), and the experiential engagement ⫻ problem-solving approach and rational engagement ⫻ problemsolving approach interaction terms. As shown in Table 2, there were statistically significant interactions between rational engagement and problem-solving approach for both creativity measures
Table 1 Descriptive Statistics and Correlations Variable 1. 2. 3. 4. 5. 6. 7.
Average creativity Above average creativity Gender Marketing internship Experiential engagement Rational engagement Problem-solving approacha
M
SD
1
2
3
4
5
6
7
2.81 45.30 0.59 0.18 3.57 3.73 0.51
0.74 21.29 0.49 0.38 0.63 0.59 0.50
— .86ⴱⴱ .20ⴱⴱ .04 .10 ⫺.04 .09
— .13 .07 .01 ⫺.06 .10
— .15ⴱ .15ⴱ ⫺.12 .02
— .15ⴱ ⫺.02 .02
— .18ⴱ .13
— .03
—
Note. N ⫽ 179. Dummy-coded variable (0 ⫽ intuitive problem solving; 1 ⫽ rational problem solving). ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01 (two-tailed). a
DANE, BAER, PRATT, AND OLDHAM
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Table 2 Results of Regression Analyses for Average and Above-Average Creativity on Problem-Solving Approach, Typical Thinking Style, and Their Interactions Average Above-average creativity creativity
Variable Gender Marketing internship Experiential engagement Rational engagement Problem solving approach1 Experiential engagement ⫻ Problem-solving approach Rational engagement ⫻ Problem-solving approach R2 F
0.19ⴱⴱ 0.01 0.04 0.15 0.08
0.13 0.06 ⫺0.04 0.18 0.09
0.07
0.06
⫺0.26ⴱ 0.08 2.14ⴱ
⫺0.32ⴱⴱ 0.08 2.04ⴱ
Note. Entries represent standardized regression coefficients when all terms are included. 1 Dummy-coded variable (0 ⫽ intuitive problem solving; 1 ⫽ rational problem solving). ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01.
( ⫽ –.26, p ⬍ .05 and  ⫽ –.32, p ⬍ .01, for average and above average creativity, respectively). The coefficients associated with the interaction between experiential engagement and problemsolving approach, however, were not statistically significant (s ⫽ .07 and .06, ps ⬎ .05).1 As suggested by Aiken and West (1991), we further analyzed the significant interactions by evaluating simple slopes at low and high levels of rational engagement. Results indicated that when rational engagement was low, the simple slopes of the regression lines had significant positive values for both average and above average creativity (b ⫽ .63, p ⬍ .05; b ⫽ 22.59, p ⬍ .01), indicating that those who described themselves as low on rational engagement were more creative when they were instructed to produce ideas rationally rather than intuitively. When rational engagement was high, the simple slope of the regression line had a nonsignificant value (b ⫽ ⫺0.39, p ⬎ .05) in the case of average creativity, but a significantly negative value in the case of above average creativity (b ⫽ ⫺14.72, p ⬍ .05), suggesting that individuals who tended to think rationally were more creative when instructed to produce ideas using an intuitive approach. The interactions are depicted in Figures 1 and 2.
Discussion This study examined whether individuals were more likely to generate creative ideas when they used a problem-solving approach that was at odds with their natural or typical thinking style. Overall, our findings provide support for the claim that thinking “off the beaten path” may be conducive to the creative process. In contrast to some lines of extant research (e.g., Garfield et al., 2001; O’Hara & Sternberg, 2001), we did not find any main effect of problem-solving approach or of the engagement measures on either of our measures of creativity. Rather, we found that individuals who did not express an affinity toward rational engagement (i.e., those who were low on rational engagement) generated more creative ideas when they were instructed to employ a rational
rather than an intuitive problem-solving approach. This interaction emerged across both of our creativity indicators—average creativity and above average creativity. Evidently, it is the interplay between the thinking style being evoked and the degree to which individuals tend to think in a rational or nonrational manner that is driving creativity. The logic underlying this finding is that individuals who find themselves in a situation in which nonstandard cognitive pathways are called upon may engage in set-breaking cognitive associations that result in elevated levels of creativity (Newell et al., 1962). Surprisingly, this logic did not extend to our other thinking style: experiential engagement. Specifically, we did not find a significant interaction involving experiential engagement with regard to either average or above average creativity. One possible explanation for this finding is that requiring individuals who do not typically think rationally to adopt a rational thinking style represents more of a novel or unusual circumstance than requiring individuals who do not express a particular affinity toward thinking experientially to adopt an experiential thinking style. As scholars have argued, the rational system of processing is engaged only through the conscious, intentional effort of the individual (Epstein, 2002; Kahneman, 2003). In contrast, experiential processing represents a more nonconscious, automatic form of cognition that is relatively effortless to employ and rely upon (Epstein, 2002; Kahneman, 2003; Lieberman, 2000). Moreover, research on the application of nonconscious processing in everyday life (Bargh, 1996; Bargh & Chartrand, 1999) suggests that individuals may be well versed in its use. Extrapolating from this research, intuiting may be a well, or even overly learned process. If so, this suggests that individuals who may not be comfortable relying solely on their intuitions may nonetheless still be quite accustomed to what it feels like to engage in experiential processing. Consequently, this processing may not be highly novel or unusual and, as a result, may fail to trigger the 1 We repeated all analyses using three additional indicators of creativity suggested by the literature (e.g., Runco, Illies, & Reiter-Palmon, 2005; Runco & Okuda, 1991; Torrance, 1974): fluency, originality, and flexibility. To assess fluency, we counted the number of ideas each participant generated that did not overlap with the ideas suggested by other participants. To derive an originality score, we first assigned to each categorized idea a frequency value—the number of times participants in our sample had generated ideas in that particular category (e.g., the category “use advertising flyers” was mentioned 138 times so we assigned each idea in that category the value 138). All uncategorized ideas received a value of 1. We then averaged the values assigned to each idea across all ideas generated by each participant. The resulting variable indicated the extent to which a participant’s ideas were low versus high in their originality. Finally, to derive a flexibility score, we counted for each participant the total number of different categories in which he or she had generated ideas. If an idea was not classified into one of the 22 categories, we counted it as its own category. Next, we repeated our regression analyses shown in Table 2 for each of these three creativity indicators. Results showed that the coefficients associated with the main effects (experiential engagement, rational engagement, problem-solving approach), the interaction between experiential engagement and problem-solving approach, and the interaction between rational engagement and problem-solving approach were not statistically significant for the fluency, originality, or flexibility measures (all ps ⬎ .05). Details of these results are available on request from the authors.
SPECIAL ISSUE: RATIONAL VERSUS INTUITIVE PROBLEM SOLVING
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2.50 2.40 2.30
Average Creativity
2.20 2.10 2.00 1.90 1.80 Rational engagement low Rational engagement high
1.70 1.60 1.50 Intuitive problem solving
Figure 1.
Rational problem solving
Interaction of problem-solving approach and rational engagement on average creativity.
activation of nonstandard cognitive pathways. In contrast, rational analysis— especially among those who prefer to avoid rational thinking—is likely to be more novel and, hence, more likely to activate nonstandard cognitive pathways. In a related vein, our results further suggest that individuals high in rational engagement are more likely to generate creative ideas when they are instructed to use an intuitive problem-solving technique. Given our theoretical arguments, however, the explanation for this finding is not immediately clear. It could be argued that thinking intuitively represents a novel thinking approach for those high in rational engagement. However, given the theoretical independence of the rational and experiential systems (Epstein, 1994; Pacini & Epstein, 1999), it is faulty to assume that those high in rational engagement are necessarily low in experiential engagement (Pacini & Epstein, 1999). Thus, when individuals high in rational engagement rely on intuitive problem solving, this does not imply that they must be thinking in a novel or nontypical manner (because such individuals may also be high in experiential engagement).
It may therefore be the case that creativity flourishes when individuals high on rational engagement are not only instructed to employ intuitive problem solving, but are simultaneously low on experiential engagement. We tested this potential alternative explanation by calculating a three-way interaction between thinking style technique, rational engagement, and experiential engagement and entering it (after controlling for all relevant two-way interactions) into the regressions equations displayed in Table 2. We found no support for this three-way interaction with respect to either average or above average creativity (s ⫽ .08 and .10, ps ⬎ .05). These results suggest that our findings are not attributable to this more complex set of relations. Finally, it may be that individuals high in rational engagement used both rational and intuitive problem solving when they were instructed to solve problems intuitively. A small body of research suggests that switching between different approaches may facilitate higher quality decision making (Agor, 1986; Hodgkinson & Sadler-Smith, 2003; Shapiro & Spence, 1997). By extension, perhaps “switching cognitive gears”
40
Above Average Creativity (%)
35
30
25
20 Rational engagement low Rational engagement high
15
10 Intuitive problem solving
Figure 2.
Rational problem solving
Interaction of problem-solving approach and rational engagement on above average creativity.
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(Louis & Sutton, 1991) may also facilitate creativity. However, this possibility is speculative given that we did not measure whether such switching actually occurred. We return to this issue in the Limitations section below.
Limitations Our study has certain limitations that are worth noting. First, our use of a laboratory design involving undergraduate students raises questions about the external validity of our findings (Cook & Campbell, 1979). As with all laboratory research, we cannot be certain whether our results generalize beyond the laboratory context or beyond the undergraduate student population. However, we believe that features of our experimental task may enhance the generalizability of our results. In particular, we designed our task based on a real-world store’s business problem. We also relied on managers from the store itself as our raters of idea creativity, as opposed to other types of raters (e.g., graduate students) who might not have been as familiar with the store’s needs and challenges. In following these methods, we attempted to ensure that our task was realistic and that participants’ creativity on the task was evaluated by individuals with the highest level of domain expertise (see Amabile, 1982). As such, we believe our study may benefit from a greater degree of realism than many other laboratory studies, thereby enhancing its generalizability to organizations. Second, our raters provided a single rating of the overall creativity of each idea (i.e., the extent to which the idea was both original and potentially useful). Although this approach is consistent with previous research (e.g., Amabile, 1982; Madjar & Shalley, 2008; Shalley & Oldham, 1997), it is not clear that our raters gave equal weighting to both dimensions when evaluating the ideas. It may be, for example, that the raters placed more emphasis on the potential usefulness of the suggested ideas than on the originality of those ideas. Even though we provided the raters with the number of ideas within each category, our supplementary analysis concerning originality suggests this might indeed be the case (see footnote 1). This analysis demonstrated that our problemsolving approach and thinking style variables had no statistically significant main or interactive effects on the originality measure. These observations suggest there may be value in “unpacking” the creativity concept (Unsworth, 2001) and obtaining separate measures of the originality and potential usefulness components. Such an approach would reduce the possibility that raters would provide unequal weightings of the components of creativity. Moreover, this approach would allow researchers to investigate whether problem-solving approaches and typical thinking styles have different effects on the two dimensions of creativity. For example, it may be that those who are low on rational engagement produce ideas of greater usefulness when instructed to produce ideas rationally, whereas those who are low on intuitive engagement produce ideas of greater originality when instructed to produce ideas intuitively. Future research is needed to systematically investigate these possibilities. Third, in categorizing many of the ideas that participants generated, we may have eliminated fine grained distinctions that could have been drawn among ideas in the data set, including ideas placed in the same category. If we had asked raters to evaluate all of the ideas in the data set without first placing ideas into categories, a greater number of distinctions may have emerged. And
more distinctions may have increased our likelihood of finding statistically significant effects for several of our creativity measures, including our supplementary measure of flexibility (see footnote 1). However, given the high level of labor and time commitment that such an approach would have required from the managers who rated participants’ ideas, we determined that some level of categorization was necessary. Fourth, we offered a reward (a $10 gift certificate) to participants for any idea they generated that the organization elected to adopt. Although the use of such incentives is not uncommon in the literature (see Baer, Oldham, Jacobsohn, & Hollingshead, 2008), previous research suggests that extrinsic rewards may be perceived by individuals as controlling and undermine their creativity (Amabile, 1996), at least in selected circumstances (e.g., Baer, Oldham, & Cummings, 2003). Therefore, it is possible that the gift certificates offered were regarded as controlling rewards by our participants and thus resulted in reduced levels of creativity across both experimental conditions in our study. However, because participants in all conditions were offered the identical gift certificate, it is not likely that this reward changed the pattern of our results. Given that rewards may have potentially dampened our effects, future research should attempt to replicate our results without offering external rewards to participants. Fifth, although we followed established research techniques for manipulating intuitive and rational thinking (Dane et al., 2009; Jordan et al., 2007; McMackin & Slovic, 2000; Wilson & Schooler, 1991), there are some limitations to these approaches. Dane and Pratt (2009) argue that without accompanying neurological or physiological measures, it may be difficult to confidently ascertain whether experiential processing (i.e., intuitive thinking) is truly occurring. Nonetheless, our manipulation check results suggest that participants did tend to formulate ideas using the specific problem-solving approach to which they were assigned. Finally, in separately manipulating intuitive and rational problem solving, our study overlooks the possibility that both intuitive and rational thinking may be necessary for creative idea generation. In designing and conducting this study, our intent was to determine whether problem-solving approaches, assessed independently, interact with individuals’ typical thinking styles to jointly enhance the creativity of ideas. Our design does not allow us to determine whether switching intermittently between different problem-solving approaches stimulates creativity. Given that both problem-solving approaches may conceivably be used in tandem to perform creativity tasks (Policastro, 1995), we believe future research studies should examine whether switching between problem-solving approaches constitutes an equally or more effective route toward fostering creativity than adopting a single, nontypical problem-solving approach.
Implications The results of this study have a number of implications, both theoretical and practical. First and foremost, the interaction effects between rational engagement and problem-solving approach suggest a role for nontypical thinking in creative idea generation. With respect to individuals who express a lack of affinity toward engaging in a rational thinking style, our results suggest that there is value in encouraging such individuals to think in a more rational manner when generating creative ideas. Our results also suggest
SPECIAL ISSUE: RATIONAL VERSUS INTUITIVE PROBLEM SOLVING
that individuals who tend to think rationally may benefit from employing an intuitive problem-solving approach on problems requiring the generation of creative ideas. Although we did not find similar interactions involving experiential engagement, the fact that we did not find any main effects involving either problemsolving approach or thinking style on any of the measures of creativity suggests that it may indeed be the interplay, and particularly, the divergence between problem-solving approaches and typical thinking styles that drives creativity. From a practical standpoint, our results suggest that to foster creativity, managers may need to create an environment in which individuals are likely to leave their natural tendencies behind and are willing to explore new, nonstandard cognitive pathways. This is not an insurmountable challenge. As our study demonstrates, with simple verbal instructions it is possible to at least temporarily affect how individuals approach a problem. Of course, to know which problem-solving approach to induce, a manager must have an accurate understanding of a subordinate’s typical way of thinking. By promoting a nontypical approach, managers may enhance creative idea generation within an organization. However, this recommendation must be interpreted with a certain amount of caution because we did not find any evidence supporting the dominance of nontypical thinking with respect to experiential engagement. Also, as our study does not speak to the temporal stability of the observed effects, it may be that the beneficial effects of nontypical thinking disappear over time. Moreover, it is conceivable that directing individuals to solve problems in a nontypical manner may alter individuals’ typical styles over time. In other words, although researchers have shown there to be reliable individual differences in rational and experiential engagement (Epstein et al., 1996; Pacini & Epstein, 1999), we do not know how stable these differences are, and whether they may shift over time because of repeated problem-solving prescriptions.
Conclusion This study contributes to the creativity literature by assessing the role of problem-solving approaches in fostering creative idea generation. Although the concepts of rational and intuitive problem solving are not new (see Barnard, 1938), scholars have only recently begun to offer empirical accounts regarding the effects of problem-solving approaches on a number of different outcomes (e.g., Garfield et al., 2001). Along these lines, we have drawn upon and extended research connecting rational and intuitive problem solving to creativity, and, in so doing, offered a multiplicative perspective on the interplay between problem-solving approaches and individual differences in thinking styles in terms of creative task performance. Our results suggest that instructing individuals to adopt a problem-solving approach that deviates from their natural thinking style may carry positive consequences for creative idea generation. More broadly, this finding suggests that scholars may benefit from considering problem-solving approaches and typical thinking styles in combination when examining the relative merits of rationality and intuition on a variety of tasks.
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Received September 9, 2009 Revision received September 9, 2009 Accepted September 10, 2009 䡲
