The Influence of Cognitive Style States on Creativity: A Dual-Process Approach

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Master Thesis

June 2015

The Influence of Cognitive Style States on

Creativity: A Dual-Process Approach

By

Pieter A.C. Hoeks

S1769294

MSc Strategic Innovation Management

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P.A.C. Hoeks

The Impact of Cognitive Styles on Creativity: Evidence from

the Dual-Process Theory

Pieter Hoeks

Abstract. This thesis tests the core assumption of the dual-process theory by empirically investigating

the impact of simultaneous activation of the experiential and rational cognitive styles, using manipulative scenarios, on individual creativity. Based on previous literature, we argue that participants in the experiential-rational condition express higher levels of creative performance compared to participants in the experiential condition, and that participants in the experiential condition express higher levels of creative performance compared to participants in the rational condition. We test these hypotheses in a sample of (under) graduate students generating creative ideas after being subtly induced to adopt a specific cognitive state by making use of real professions. There are no significant relationships between the measures of creativity and the different cognitive states. Mean analysis, however, indicates that individuals in the experiential-rational state, do report higher levels on both Fluency and Flexibility. Additionally, individuals in the Rational condition report the highest levels of Originality.

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1. Introduction

Several researchers have argued that creativity constitutes humankind’s ultimate resource (Toynbee, 1964). Nowadays, this statement seems even more accurate in a global society where the focus on individual creativity has increased due to turbulent changes in the business environment, fierce competition in the global markets, and the knowledge base economy that has made jobs more complex and mobile (Joo, McLean, & Yang, 2013).

As a result of this view, researchers and practitioners have studied methods of increasing the idea output of individuals and groups (Dean et al., 2006). Particular emphasis has been placed on improving the tools and methods used to support idea production because the ability to generate ideas is critical to promoting innovation and nurturing managerial problem-solving abilities (Dean et al., 2006). Generally, creativity is defined as the generation of ideas, insights, or problem solutions that are new and meant to be useful (Amabile, 1983; Paulus &Nijstad, 2003; Sternberg & Lubart, 1999). Taking the vigorous evidence on creativity into consideration, it is clear that it is of high managerial and societal relevance to identify means that stimulate one’s creativity, and thus spark the creative process as route to organizational innovation.

Prior research on stimulating individual creativity has focused on social psychology based factors (Dennis & Wixom, 2002), or individual characteristics such as, tenure, gender, and educational background (Ancona & Caldwell, 1992; Hulsheger et al., 2009; Lovelace et al., 2001). Although these studies contribute to the current understanding of fostering creativity in the business environment, they fail to address deeper-level variables influencing creativity. Studies that do address deeper-level variables, such as found in the cognitive and social psychology literature (e.g., K irton, 1976; Miron et al., 2004; Scott and Bruce, 1994), have focused on the individual level (e.g., cognitive style traits), analyzing the impact of different cognitive styles on idea generation, creativity, and innovation, from a rather one-dimensional or bipolar view.

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suggested that there may be two architecturally (and evolutionarily) distinct cognitive styles underlying these dual-process accounts (Evans, 2008), suggesting that both systems can operate simultaneously, independently and interactively (Kahneman, 2003).

So far, few studies have been dedicated to better understand the interplay between rational and experiential cognitive styles, as suggested by the dual-process theory, on creativity.

Literature that did relate to this relation has yielded, till now, inconsequent findings (Hennessey & Amabile, 2010). As such, researchers (Nijstad et al., 2010) argue that the creative thinking described by their model is primarily the product of the rational cognitive style. In accordance, Wiley and Jarosz (2012) state that higher cognitive ability and more analytic cognitive style is associated with increased creativity. In contrast, several lines of evidence have shown that too much focus, analytical thought, can actually harm creative problem solving. For instance, researchers (Scott and Bruce, 1995; Smith and DeCoster, 2000; Yates, 1999) have found creativity to be positively associated with the experiential versus rational cognitive style. These contradicting findings invite for further research. Also, previous research in the field of cognitive psychology has rather focused on the measurement of cognitive style traits instead of cognitive style states. Especially work focusing on the simultaneous activation of one’s cognitive style state is scarce, leaving a gap for further exploration.

This study tends to fill this gap by investigating the extent to which one’s cognitive style, manipulated via a scenario-based task, impacts one’s creativity. Specifically, by using scenarios to simultaneously activate the two cognitive styles (e.g., experiential and rational), we aim to deviate from previous research (e.g., Dane et al., 2011; Sagiv et al., 2014) who used scenarios in which participants, for instance, were explicitly instructed to adopt a certain cognitive style (e.g., “Generate ideas based on your gut instinct”; “Be as analytical as possible”). Our scenarios aim to induce a cognitive state to an individual by making use of real professions that implicitly require specific thinking styles. In this way, we intend to manipulate, in a more subtly way, individuals’ cognitive style states. Ultimately, this paper aims to contribute to the stream of cognitive and social psychology by testing the core assumption of the dual-process theory by empirically investigating the impact of simultaneous activation of the experiential and rational cognitive styles, using manipulative scenarios, on individual creativity. Moreover, this paper seeks to answer which activated cognitive style state will be most conductive to creativity.

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experiential and rational thinking (Epstein et al., 1996). Then participants were randomly assigned, individually, to different methods of cognitive styles manipulation. After each manipulation, participants were asked to complete a creativity task. Finally, participants were asked to fill out a manipulation check questionnaire. In prior speculation, we expect the participant who is manipulated to be experiential will be more creative than the participant who is manipulated to be rational, and the participant who is manipulated to be experiential will be less creative that the participant who is manipulated to be experiential-rational.

The remainder of this thesis is structured as follows. First, an overview of the existing literature is presented concerning both research on creativity and cognitive style. Second, the development of the hypotheses is presented, which are based on the insights of the dual-process theory on creativity. After the hypotheses, the methodology of this study is discussed, followed by the results and data analysis section. This paper finalizes with an overview and discussion of the main theoretical and managerial findings. Also, research limitations and suggestions for future research will be pointed out.

2. Literature and Background

Since employee creativity is an important source of organizational innovation and competitive advantage (Amabile, 1988, 1996; Oldham & Cumming, 1996; Shalley, 1991; Zhou, 2003), organizations are increasingly seeking to find ways to foster individual creativity (Oldham, 2003). As such, general quantitative empirical research approaches to explore individual creativity include laboratory studies, field surveys, and longitudinal approaches. In accordance to previous work, we quantify creativity by focussing on the measurement of: (1) fluency, described as the total number of ideas; (2) flexibility, number of used categories; and (3) originality, which refers to an idea or suggestion that is infrequent, novel, and uncommon (Amabile, 1983; Guilford, 1967; Torrance, 1993; De Dreu, Baas & Nijstad, 2008). The remainder of this section will shed light on the extant body of literature concerning creativity and the main theories applied are introduced.

2.1 Individual Creativity

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In their work on creativity, Amabile & Conti (1997) present a motivational component as important factor in their famous three-component model of individual creativity. Both authors suggest that individual creativity depends on skills in the task domain, skills in creative thinking, and motivation. If any is absent, creativity will be absent (Amabile & Conti, 1997). Following this line of reasoning, mounting empirical evidence has demonstrated that individuals are more creative when they possess higher levels of these components (Conti, Coon, & Amabile, 1996; Ruscio, Whitney, & Amabile, 1998). Moreover, evidence from the same school of researchers indicate that intrinsic motivation is one of the most important and powerful influences on employee creativity (Amabile, 1988, 1996; Amabile et al., 1996; Shalley, 1991, 1995). Ryan & Deci (2000) confirm the importance of motivation and state that intrinsic motivation results in high-quality learning and creativity. In addition, Mumford (2003) assumes creativity to be strongly affected by interest in tasks for their own sake (“intrinsic motivation” or “Intrinsic task interest”).

Within the creativity literature, some object that the distinction between personal traits and cognitive ability is artificial (Heim, 1970). However, cognition and personality traits have traditionally been seen as distinct domains. Intelligence is construed as a set of aptitudes and abilities, where personality is viewed as a collection of characteristic dispositions (McCrae, 1987). A voluminous literature has documented the importance of both these aspects on creativity (Barron & Harrington, 1981).

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with self-report measures of creativity (Batey et al., 2010). Jauk et al. (2013), for instance, obtained evidence for a more nuanced view of the interplay between personality factors and intelligence, suggesting that once a intelligence threshold is met, personality factors become more predictive for creativity (Jauk et al., 2013).

Notwithstanding the large extent of literature that has focused on individual characteristics such as motivation, personality traits, and cognitive ability, research that has addressed deeper levels of creative thought and how they affect creativity are scarce, conflicting, and incomplete. We discuss and review the current literature in the next section. Our hypotheses will be drawn after presenting the main findings in the field of cognitive psychology.

2.2 Dual-Process Theory – Two Systems of Information Processing

In our effort to investigate the extent to which one’s cognitive style, manipulated via a scenario-based task, impacts one’s creativity, we draw upon the insights derived from dual-process theory. This theory of social cognition emerged in the 1980s (Chaiken, 1980; Petty & Cacioppo, 1981) and developed in popularity to form the dominant paradigm for the last 20 years or more (Evans, 2008). The central assumption on which dual-process theory is based is the view that experiential and rational approaches to information processing are associative and parallel.

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experiential cognitive style is regarded as contributing to experience-based decision-making and is considered as largely independent of cognitive ability. On the other hand, there is the rational system, that is analytic and reflective, primary verbal, conscious and functions via people’s understanding of the conventional rules of logic (Epstein, 1994; Kahneman, 2003; Stanovich & West, 2000; Salton, & Sharabi, 2002). It is slow and demanding, thus, better suited for delayed actions and complex, dispassionate analysis (Epstein, 2002; Evans, 2008). Recent research conducted by Snowden and colleagues (2015), state that responses that are based on the rational cognitive style are often regarded as normative and rational, as contributing to consequential decision-making, and as correlated with cognitive ability. appendix A provides an overview of the different labels and clusters of attributes associated with dual process thinking.

The findings of several studies provided support for the independent existence of the experiential and rational systems as suggested by CEST (e.g., Denes-Raj & Epstein, 1994; Epstein et al., 1992; Epstein et al., 1996; Kirkpatrick & Epstein, 1992). For instance, in their research conducted under norm theory, Epstein and colleagues (1992), have provided impressive evidence of an “if only” effect associated with post outcome processing of aversive events that are highly consistent with formulations of CEST. In another study, Epstein (1993) observed that the operation of the experiential system was most clearly ascertained when people were confronted with emotionally significant real experiences and when conditions were established that circumvented their need to present themselves as rational. Denes-Raj and Epstein (1994) found that the two systems normally engage in a consistent interaction but can conflict from time to time, causing a clash between feelings and thoughts. Also, Epstein and colleagues (1996) showed that heuristic processing across a sample of vignettes was primarily a function of individual differences in experiential processing, but was also influenced by rational processing, thus delivering improved evidence on the assumption that the two independent systems jointly determine behaviour.

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3. Hypotheses: A Dual-Process account of Creativity

Various authors have recognized cognitive style as core characteristic of employee creativity (Kirton, 1976; Scott & Bruce, 1994; Tierney et al., 1999; Amabile, 1988; Woodman et al., 1993). Although there is considerable consensus on the importance of cognitive styles on creativity, there is an ongoing debate on which cognitive style (e.g., experiential or rational) is most beneficial in nurturing creativity. Our arguments for sympathizing the view that the experiential cognitive style is most beneficial to creativity are based on previous findings in the literature.

Norris and Epstein (2011), found support for their hypotheses that the experiential thinking style is significantly associated with a variety of objective non intellective criterion measures of desirable attributes. Four significant relationships were found between an experiential thinking style and the objectively measured favourable attributes of creativity (e.g., aesthetic judgment, humour, and intuition) (Norris & Epstein, 2011). Other studies (e.g., Smith & DeCoster, 2000; Yates, 1999), found the same stimulatory relationship between the experiential cognitive style and creativity. Overall, these authors have in common that they suggest that intuitive thinking involves linking various areas of thought together and that intuitive individuals rely more on their imagination. The experiential person tends to process information from various paradigms simultaneously, and is therefore more likely to come up with original and novel solutions to problems (Scott & Bruce, 1994). Moreover, Garfield and colleagues (2001) found direct support for their hypotheses which stated that Intuitor-Feelers will generate more novel and more paradigm-modifying ideas than Sensor Thinkers. Thus, providing sound empirical evidence supporting the link between intuitive problem-solving and creativity (Garfield et. al, 2001). On the other hand, Scott and Bruce (1995) provided support for prior conceptualizations of the influence of individual cognitive style on the process of innovation. Their study to measure decision-making style amongst a sample of military officers and MBA students suggested that individuals who approach problems in a rational manner are less likely to be innovative (Scott & Bruce, 1995). Also, analytic thinkers usually rely on a set of consistent rules and disciplinary boundaries, using logic and rationality. As such, analytic individuals tend to follow regular methods and processes, and therefore suggest fairly conventional solutions to problems (Sagiv et al., 2009). Accordingly, we expect that experiential individuals are more creative than rational individuals. Thus, we hypothesize:

𝑯𝟏: Individuals manipulated to be experiential will be more creative compared to individuals

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As presented above, it is generally accepted that the dual-process theory invokes two processing systems that can work simultaneously, independently, and interactively to one another (Kahneman, 2003). However, the originators of this two-system view have recently considered it as incompletely specified (Evans, 2009; Stanovich, 2009). Or as Sloman (1996) argued: “Like all good dichotomies, the cognitive style one might eventually decompose into a trichotomy of associative, rule, and mental model systems” (p.6).

We sympathize this view and assume, due the architecture of REI, that the experiential-rational style is a style in which both processing styles (e.g., experiential and experiential-rational) are simultaneous activated. We argue that this simultaneous activation results in a relative equal contribution along both dimensions.

Based on this equal distribution, we assume that individuals, manipulated to have both styles simultaneous activated, can overcome several weaknesses of the sole experiential cognitive style with regard to creativity. As such, experiential-rational individuals can overthrow, in comparison to experiential individuals, struggles to solve problems that require logical analysis by relying on influences from the simultaneous activated rational processing style (Epstein et al., 1996). Moreover, having a rational counterpart simultaneously activated, helps experiential individuals to be more focused on tasks and provide answers that are more implementable (Beaty & Silvia, 2012). In addition, Lin et al. (2012), argue that the ability to generate plausible solutions in creative problem solving reflects both novelty and appropriateness, thus requiring benefits of the experiential processing style, as well as the rule-based, resource-limited rational cognitive style.

A second line of reasoning is, that individuals having both styles simultaneously activated, can benefit from a cooperation between the two styles in order to compute sensible answers (Evans, 2007). Given that both problem-solving approaches may conceivable be used in tandem to perform creative tasks (Policastro, 1995), we argue that experiential-rational individuals benefit from the best of both worlds. Accordingly, the experiential-rational individual can benefit from its rational counterpart for its effectiveness in fostering creative ideas (e.g., Couger, 1995; Kaufmann & Vosburg, 1997; Weisberg, 1986), and the ability to generate new ideas or solutions by proceeding in a series of sequential steps that allows for effectively addressing problems (Janis & Mann, 1977). On the other hand, see hypothesis 1, individuals in an experiential-rational state can benefit from processes that are normally only active in individuals having their experiential state activated. For example, the ability of experiential individuals to rely on their imagination in order to come up with creative thoughts (De Coster, 2000).

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operation of the experiential processing style (Epstein, 2010). As such, the inferential, rational mind and the learning, and the experiential mind each has its advantages and disadvantages (Epstein, 2010). Accordingly, we argue that individuals in an experiential-rational cognitive style can overcome disadvantages of the experiential system by relying on advantages of the other system and vice versa. Therefore, we expect that experiential individuals are less creative than experiential-rational individuals. Thus, we hypothesize:

𝑯𝟐: Individuals manipulated to be experiential will be less creative compared to individuals

who are manipulated to be experiential-rational.

4. Methodology

4.1 Participants and design

90 students of a Dutch University, 48 (53.3%) men and 42 (46.7%) woman, with an average age of 22 (𝑀𝐴𝑔𝑒 = 21.87, SD = 2.26) participated in a three-part study for either course credits or a cash

payment. Students were attracted by flyering in the University building, advertisements on social media, and a notification on the University’s online experiment platform. Students from different faculties and with different nationalities were recruited in order to prevent homogeneity and enabled us with a greater variance of our data. Participants were randomly assigned to one of three different manipulations (e.g., experiential condition, rational condition, or experiential-rational condition) in which we aimed to induce a cognitive state to an individual by making use of real professions that implicitly require specific cognitive resources. The dependent variable was assessed by looking at (1) fluency; (2) flexibility; and (3) originality.

4.2 Procedure

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creativity task was handed out in which the participants were asked to generate possible ways to improve the quality of teaching in the faculty. The creativity task was withdrawn after 20 minutes and followed by a manipulation check with the instruction that once completed, the participants may exit their cubical and deposit the check by one of the researchers. Participants were then debriefed, paid and dismissed. All tasks in the lab were performed by pen and paper.

4.3. Independent Variables

Before presenting the different manipulative tasks, a general cover story was presented in which the context of the tasks was introduced (appendix C). This introduction explained the scarcity of student housing in a Dutch student town, especially amongst exchange students who are often not familiar with the Dutch language, prices, and other rent-related policies. Then a situation was outlined that the Dutch University owned several buildings that currently served no purpose. As such, the intention of the University was to prepare these empty buildings to accommodate exchange students. The general introduction ended with the statement that the University aimed to get feedback from students with regard to specific preparations required for student housing. After the general introduction, we aimed to manipulate cognitive style by a scenario-based task based on real professions. A same picture of an empty room was presented in each scenario on which the participants could base their answers.

Experiential Scenario: Participants in the experiential scenario were asked to imagine themselves as interior decorators. First a brief job description of the different activities of an interior decorator was presented guided by catchwords that induced the activation of the experiential cognitive style (e.g., artistic approach, expressive and sensitive, look and feel etc.). Then participants were asked to describe how they would decorate the room presented on the picture (e.g., floor coverings, furniture, and other items) in order to achieve an aesthetic outcome.

Rational Scenario: Participants in the rational scenario were asked to imagine themselves as interior engineers. As in the experiential task, a brief job description was given guided by catchwords that induced the activation of the rational cognitive style (e.g., analytic and logical perspective, down to earth and precise, outstanding sense of logic etc.). Note that this description exactly mirrored the previous scenario, so that the level of catchwords, information, and task guidance was the same. Then participants were asked to present a calculation about the cost involved in the renovation of the room (e.g., man-hours, building materials, and other estimates) in order to achieve a feasible outcome.

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style. The catchwords in this scenario were a combination of the words used in the previous two scenarios. Then participants were asked to describe how they would decorate the room (e.g., floor coverings, furniture, and other items) and to present a calculation about the costs involved in its renovation (e.g., man-hours, building materials, and other estimates) in order to achieve an aesthetic and feasible outcome. See appendix D for the different scenarios as we have presented it to our participants.

4.4. Control Variables

Cognitive style trait

The cognitive style trait of the participants was measured according to the self-reporting measure tool of Pacini and Epstein (1999) and is used as a control for testing our hypothesis. This Rational-Experiential Inventory (REI) consisted of 24 items divided over two subscales. First, 12 items of the Faith in Intuition (FI; Pacini et al., 1996) scale were used to measure the extent to which participants process information intuitively. Second, 12 items of the Need for Cognition (NfC; Cacioppo & Petty, 1982) were used to measure the extent to which participants process information analytically. The reliability and validity of the REI has been supported by Pacini and Epstein (1999). Also, discriminant validity has been showed, as indicated by the different relations Pacini and Epstein (1999) found with a variety of variables. Accordingly, a reliability analysis was conducted to screen if the found factors are reliable. Both factors report a Cronbach’s Alpha higher than .70 (appendix E). Nunnaly (1978) has indicated .70 to be an acceptable reliability coefficient, so we can assume that internal consistency of the different items is reliable.

Gender

Gender of the participants was established by one of the general questions in the online questionnaire and was measured with a binary scale in which male = 1 and female = 2.

4.5 Dependent Measures

Creativity is assessed by looking at Fluency (i.e. total number of ideas); Originality (i.e., new ideas), and; Flexibility (i.e., number of used categories).

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they could think of. Fluency was assessed by an individual count of the number of creative thoughts generated per participant. In addition, two independent raters rated for originality and flexibility. To obtain measures of rated originality, independent coders rated each unique idea for originality, being defined as an idea or suggestion that is infrequent, novel, and uncommon (De Dreu et al., 2008). We used a 5-point Likert scale ranging from 1 (Not original at all) to 5 (Very original). To get at Flexibility, we assigned each unique idea to one of seven categories presented by De Dreu and colleagues (2008). See appendix F for an overview of the different categories.

Interrater agreement for both originality and flexibility, respectively (.96) and (.90), were excellent following the criteria of Cicchetti and Sparrow (1981). Individual differences were solved through discussion.

5. Results

This section describes our results by analyzing the data. First, the bivariate correlation matrix is presented together with a check to see whether our data meets the assumption of collinearity. Second, a simple model will be presented in which we analyze the relationship between the variables using univariate analysis of variance. Thereafter, we extent our model to analyze the effect of potential confounding factors using ANCOVA analysis.

5.1 Descriptive Statistics

Descriptive statistics are summarized in appendix G. In this research, the standard deviations of the dependent and control variables are relatively low. However, the standard deviation of one of the dependent variable, in specific, Fluency, is rather high, which suggests large differences in number of ideas generated by our participants.

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was not a concern since all variance inflation factors (VIF) were below the cut-off value of 10 as suggested by Field (2013).

Table 1

Correlations Matrix amongst Dependent, Independent, and Control Variables

Variable 1 2 3 4 5 6 7 8 1. Conditionnumberᵃ 1 2. Fluency .13 1 3. Originality -.09 -.03 1 4. Flexibility .09 .75** -.09 1 5. Instructional Check -.31** .07 .22* -.09 1 6. Experiential CS trait .04 .02 .03 .09 -.04 1 7. Rational CS trait -.09 .01 .08 .15 .03 .23 1 8. Gender 1 = male .03 .07 .09 -.05 .23* .02 -.24* 1 Note. N = 90.

ᵃDummy-coded variable (1 = experiential condition; 2 = rational condition; 3 = experiential-rational condition) *p< .05. **p< .01 (two-tailed)

5.2 Manipulation check

To evaluate the degree to which participants complied with our scenario approach manipulation, each participant responded to four items adapted from Dane et al. (2009) in which response options ranged from 1 (definitely not true) to 5 (definitely true): Experiential check 1: “I expressed most of my ideas based on my inner feeling and immediate reactions”; Rational check 1: ”I expressed most of my ideas based on a logical and systematic way of thinking”; Experiential check 2: “I relied on my gut instinct, and; Rational check 2: I analyzed all information in detail.” See appendix I for the full manipulation check.

Univariate analysis of variance for the manipulation checks revealed no significant main effects between the different conditions (e.g., Experiential, Rational, and Experiential-Rational) on all the manipulation checks. Experiential check 1, F (2, 87) = 0.19, p = .83, ƞ² = .00, experiential condition (M = 3.77, SD = .94), rational condition (M = 3.90, SD = .80), and experiential-rational condition (M = 3.87, SD = .90). Mean comparison on this first experiential check indicate, in contrast to prior expectations, that participants in the rational condition expressed, on average, more ideas based on their inner feeling and immediate reactions.

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Rational check 1, F (2, 87) = 0.93, p = .40, ƞ²= .02, experiential condition (M = 3.63, SD = .77), rational condition (M = 3.33, SD = .96), and experiential-rational condition (M = 3.47, SD = .85). Mean comparison suggest, again contrasting prior expectations, that participants manipulated in the experiential condition expressed, on average, more ideas based on a logical and systematical way of thinking.

Rational check 2, F (2, 87) = 0.30, p = .77, ƞ²= .01, experiential condition (M = 3.30, SD = .92), rational condition (M = 3.43, SD = 1.04), and experiential-rational condition (M = 3.27, SD = .83). Mean analysis for this second rational check complied with prior expectations, such that participants in the rational condition, indeed analyzed, on average, the information in more detail than participants in the experiential condition. However, in contrast to prior expectations, participants in the experiential-rational condition, analyzed, on average, the information in less detail compared to individuals in the experiential condition. Results from these checks indicate that we cannot assume that our participants were significantly induced to adopt a certain cognitive style. Table 2 summarizes the mean analysis.

Table 2

Means and Standard Deviations for Manipulation checks Manipulation Type

Experiential Rational Experiential-rational

Variable M SD M SD M SD

Experiential check 1 3.77 .94 3.90 .80 3.87 .90

Experiential check 2 3.07 .87 3.27 .83 3.33 .76

Rational check 1 3.63 .77 3.33 .96 3.47 .82

Rational check 2 3.30 .92 3.43 1.04 3.33 .92

Note. N = 90. Experiential Condition, N = 30; Rational Condition, N = 30; Experiential-Rational Condition, N = 30.

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for the experiential and rational condition were mirrored, where the experiential-rational condition existed of a combination of the categories used in the experiential and rational condition. See

appendix J for an overview of the categories.

Another univariate analysis of variance was conducted to check the variance between instructional manipulation check scores and condition numbers. Results indicated a significant effect between the manipulation types and instructional manipulation check scores, F (2, 87) = 5.46, p < .05, ƞ²= .11. Post hoc comparisons using the Bonferroni test indicated that the mean score for the experiential condition (M = 3.87, SD= .78) was significantly different (p < .05) than the rational condition (M = 3.20, SD = 1.19). Moreover, the comparison between the experiential condition and experiential-rational condition (M = 3.10, SD = .92) also proved to differ significantly (p < .05). However, the rational condition did not significantly differ from the experiential-rational condition (p = 1.00). Taken together, these results suggest that participants in the experiential condition better understood the cognitive manipulation task compared to both the rational and experiential-rational condition. However, it should be noted that participants in the rational condition do not appear to differ significantly from participants in the experiential-rational condition with regard to the extent they understood the cognitive manipulation task. Based on these findings, we conclude that the manipulation was successful. See appendix K for the results of the ANOVA and Bonferroni.

5.3Hypothesis Check

To test our hypothesis, we start to examine the effect of the different manipulation types on creativity using univariate analysis of variance on all three categories of creativity (e.g., fluency, originality, and flexibility). To be able to conduct a univariate analysis, the dependent variables had to approximate normality. Accordingly, Fluency and Originality were transformed using a log10 transformation. After analyzing this rather simple model, we sought to extent our model by including potential confounding factors. More specifically, we sought to control for cognitive style traits, measured according the experiential (FI) and rational (NfC) scale, and gender.

First, Log10 Fluency was analyzed. Levene’s test showed that the variances between the condition types are homogeneous (.64). Additionally, the ANOVA results in appendix L table 1,indicate that there is no significance difference in the number of ideas generated between the manipulation types using a 95% interval: F (2, 87) = .96, p = .64, ƞ² = .02. A closer inspection of the means indicated that participants manipulated in the experiential-rational cognitive style generated more ideas, on average (M = 2.10, SD = .42), compared to both individuals manipulated in the rational (M = 2.01, SD = .42), and experiential (M = 1.94, SD =.46) cognitive style.

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Figure 1

Mean Creativity (Fluency, Originality, and Flexibility) for participants in the Experiential, Rational, and Experiential-Rational condition. Error bars denote one standard deviation around the mean.

value (p < .5) which indicates that the assumption of homogeneity of variance is not met. However, researchers (Boneau, 1960; Glass et al., 1972), indicating that univariate group analyses are generally robust to moderate violations of homogeneity of variance as long as the sample size in each group are equal. The ANOVA results in appendix L table 2, indicate that there is no significant difference in the originality of ideas generated between manipulation types using the same confidence interval: F (2, 87) = 1.79, p = .17, ƞ² = .04. Again, a closer inspection of the means was performed which revealed that participants manipulated in a rational cognitive style covered, on average, the most categories in their answers (M = .37, SD = .23), followed by participants manipulated in the experiential cognitive style (M = .31, SD = .18), and lastly, participants in the experiential-rational cognitive style (M = .28, SD = .13).

Finally, the effect of the different manipulation types on Flexibility was analyzed. Levene’s test of equality variance is not significant (.81). Also, results of the ANOVA analysis, in accordance with the other two dependent variables, failed to report significant results, F (2, 87) = .49, p = .61, ƞ² = .01. Appendix L table 3, presents the ANCOVA results, where figure 1 visually displays the means.

The next step in our analysis is to control for potential factors that might predict the outcome of our dependent variables. As such, the experiential (FI) scale and rational (NfC) scale are included in our model. Also, gender is included as dummy (1= male).

0 1 2 3 4 5 6

Log10 Fluency Log10 Originality Flexibility

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First, Log10 Fluency was analyzed. Levene’s test showed that the variances between the condition types are homogeneous (.61). Additionally, the ANCOVA results in appendix M table 1, indicate that there is no significant difference in the number of ideas generated between the manipulation types after controlling for cognitive style trait and gender using a 95% confidence interval, F (2, 84) = 1.03, p = .36, ƞ² = .02.

The same steps were applied to Log10 Originality. Again, in accordance to the simple model, Levene’s test reported a significant value (p < .001) which indicates that the assumption of homogeneity of variance is not met. However, equality of sample size between condition numbers indicate that ANCOVA is robust to violations of homogeneity (Boneau, 1960). Though, ANCOVA analysis could not report any significant after the inclusion of controls: F (2, 84) = 1.87, p = .16, ƞ² = .04. Appendix M table 2, sums up the ANCOVA results assessing Log10 Originality.

Finally, the effect of different manipulation types on Flexibility was analyzed. Levene’s test of equality variance is not significant (.67). Also, results of the ANCOVA analysis, in accordance with the other two dependent variables, failed to report significant results, F (2, 84) = .57, p = .57, ƞ² = .01, see

appendix M table 3.

In sum, these results suggest that there are no significant differences between the different condition types with regard to 1; the number of creative thoughts generated, 2; the originality of creative thoughts generated, and 3; the number of creative categories used, after controlling for one’s cognitive style trait and gender. In addition, a directional test of means for each measurement of creativity revealed different directions as previously hypothesized. As such, participants did not score significantly higher on both fluency and originality after being manipulated in an experiential cognitive state compared to individuals manipulated to adopt a rational cognitive style. Moreover, as hypothesized, participants in the experiential condition were more flexible compared to participants in the rational condition. However, this difference failed to report any significance. Therefore, no evidence could be provided in supporting our first hypothesis. Thus, we reject 𝐻1 . According to

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6. Conclusion

This section is structured as follows: first a wrap up of our intentions before conducting this research are presented. Second, we provide our core findings. Then, we present our main theoretical and methodological implications followed by a set of managerial implications. Thereafter, several limitations concerning our research design are presented together with directions for further research in both social and cognitive psychology.

6.1 Discussion

The main aim of this study was to provide insights on ways to stimulate individual creativity by addressing deeper level variables. As such, dual-process theory, in specific, Cognitive-Experiential Self-Theory (CEST; Epstein, 1994; Epstein & Pacini, 1999) was applied as main theoretical lens through which we studied the effects of cognitive styles on individual creativity. Central in applying CEST as main theory is the assumption that both cognitive styles (e.g., experiential and rational) can operate simultaneously, independently and interactively (Kahneman, 2003). We choose this angle of perspective since no previous work exists that investigates ways to stimulate individual creativity from the perspective of CEST. Also, inconsistent findings of previous work on which cognitive style is most beneficial to promote creativity invited us to perform this research.

Specifically, we sought to subtly induce participants to adopt a cognitive style by making use of real professions, thereby deviating from previous research that gave specific instructions to adopt a cognitive style (Dane et. al., 2011). We hypothesized, based on previous literature, that individuals induced to adopt a experiential cognitive style will be more creative than the participant induced to adopt a rational cognitive style. In addition, this research investigated the notion that there might be a third way of processing information along the experiential and rational continuum (Sloman, 1996; Evans, 2009; Stanovich, 2009), labeled, the experiential-rational cognitive style, in which both processing styles are simultaneously activated. Accordingly, we hypothesized that participants induced to adopt a experiential cognitive style will be less creative compared to the participant induced to adopt an experiential-rational cognitive style since experiential-rational participants can benefit from best of both worlds.

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23 P.A.C. Hoeks

and sequential fashion, experiential individuals tend to generate ideas across more categories and thus score higher on Flexibility. However, in contrast to findings of Nijstad et al. (2010), who state that rational thinking primarily leads to ideas that are highly accessible and closely related to existing concepts and ideas, and thus not to originality, our means indicate the opposite direction. This suggests that participants induced to adopt a rational cognitive style generated the most original ideas. A possible explanation for this contrasting effect might be found in the initial manipulation checks derived from Dane et al. (2009). Means of both experiential manipulation checks revealed that participants in the rational condition reported highest levels of intuitive reasoning and expressed most of their thoughts on their inner feelings and immediate reactions in comparison to participants in the experiential condition. Given these contradicting results, it is likely to assume that our manipulation based on the use of real professions might have failed for inducing a rational cognitive style. This failure might be explained by the characteristics of the rational thinking style in such way that requiring individuals who are low on rational engagement to adopt a rational thinking style represents more of an abnormal or novel circumstance than requiring individuals low on experiential engagement to adopt an experiential thinking style (Dane et al., 2011). Manipulating by making use of real professions may not have been sufficiently novel or abnormal to induce participants into a rational thinking style since this thinking style is only engaged through the conscious, intentional effort of the individual (Epstein, 2002; Kahneman, 2003).

Means on both Fluency and Flexibility indicate, according to our prior reasoning, that the experiential-rational cognitive style is most beneficial to creativity. These findings justify our claim that individuals having both cognitive styles simultaneous activated may benefit from a cooperation between the two styles in order to compute sensible answers. Additionally, it seems that when both styles are activated simultaneously, participants had the advantage of the best of both styles. These findings contradict previous authors (E.g., Sloman, 1996; Epstein, 1994; De Neys & Glumcic, 2008), who argue that the sole operation of one’s cognitive style is most beneficial to enhance creativity, thereby preventing a clash between the head and the heart.

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Altogether, our proposition that the experiential-rational cognitive style is most beneficial for creativity should be interpreted with care. Fair consideration exists whether our manipulation actually worked. Therefore, we limit our advice to the notion that it seems that each cognitive style has its own advantages and disadvantages with regard to different constructs of creativity. However, simultaneous activation of both rational and experiential cognitive styles, seemed beneficial in two out of three cases.

6.2 Theoretical and Methodological implications

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from this activated cognitive style. Future research could reconsider the amount of time to induce participants to adopt a cognitive state.

6.3 Practical Implication

Our distinction between cognitive style and their effect on creativity measures are relevant to managerial practices. First, it suggests that managers should be aware of the core purpose of a creative task on beforehand. For example, it is useful to consider the different stages involved in creative thinking. There are clear qualitative differences between stages of the new product design cycle, and given the complexity of creativity, it is the case that different models of dual-process thinking are more or less useful during different stages (Allen & Thomas, 2011). For example, in the first stage of the NPD process, the idea generation stage, where the quantity of generated ideas are more relevant than the quality of ideas generated (Smith et al., 1999), our direction of means concerning condition number and creativity scores suggest that employees induced to adopt an experiential-rational cognitive style will generate the highest number of ideas covering a wider spectrum of categories. In addition, given our results that one’s cognitive style state is not affected by one’s cognitive style trait, indicates that even when employees have a stable preferred way of processing information, they can be brought into a context where a different cognitive state is activated. This implies that managers are not bound by the cognitive style traits of their employees when composing new product development teams. Second, as our study intended to demonstrate, activating one’s cognitive style does not necessarily expend a lot of organizational resources. Simple exposure to well selected stimuli might be sufficient to activate one’s cognitive state, or states, in order to exert a higher level of creativity on a specific task. A replication of this study, using a different way to subtly induce participants to adopt a cognitive state, would be recommended for the outside world to empirically justify our claim. In addition, managers should be aware that the duration of manipulation is yet to be investigated.

6.4 Limitations and future research

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Second, we offered a reward (either course credits or a cash payout of €8) to participants for participating in our research. Although the use of such incentives are not uncommon in the literature (See Dane et al., 2011), research conducted by Amabile (1996) suggest that extrinsic rewards are actually detrimental for individual creativity. Moreover, there might be a biasing effect between both extrinsic rewards. Participants who are rewarded with course credits may have a different incentive (e.g., requirement to pass a course), compared to participants selecting a cash payout. Future research can overcome this limitation by offering only one type of reward or including type of payout as control variable.

Third, our research design made use of real professions to subtly induce participants to adopt a certain cognitive style, which deviated from previous and more established techniques for manipulating experiential and rational thinking (Dane et al., 2011; Dane et al., 2009). Also, an alternative manipulation check was assessed to determine whether participants successfully adopted a cognitive style. This alternative check was performed by a single rater, which might raise questions about the objectivity of scores. Fair considerations exist whether participants truly adopted a cognitive style. Especially since Dane and Pratt (2009) argue that without accompanying neurological or psychological measurements, it may be difficult to ascertain whether or not the manipulation was successful or not. Future research may focus on more sophisticated ways of performing manipulation checks to guarantee the manipulation of participants. In addition, increasing the number of raters would reduce the possibility of subjectivity.

Fourth, only 90 participants participated in our experiment which is a fairly low sample size. This small sample size makes it harder to generalize findings for larger populations. Additionally, this research was limited to a Dutch University. Although a fair amount of different nationalities were represented in this study, questions with regard to generalizability are just. Future research may seek to increase sample size in order to yield more generalizable and sound results. Also, future research can be conducted beyond the involvement of students and focus on employees within a business setting instead.

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human mind. Additionally, if future evidence supports this third way of processing information, it would be of high societal relevance to further investigate the effects of simultaneous activated cognitive styles on creativity.

A final proposition is to look at creativity along a broader spectrum of constructs. As we have demonstrated in this study, there seem to be deviations in scores on the different measurements of creativity (e.g. fluency, originality, and flexibility) as a result of the activation of a specific cognitive style. A future research direction is to construct a map of guidance that represent validated measurements of creativity and which cognitive style is most beneficial to render the highest score.

Acknowledgements

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Appendix A: Labels attached to Dual-Process in the Literature

Table 1

Labels Attached to Dual-Processes in the Literature, Aligned on the Assumption of a Generic Dual-System Theory

Table 2

Clusters of Attributes Associated with Dual mSystems of Thinking

System 1 System 2

Cluster 1 (Consciousness)

Unconscious (preconscious) Conscious

Implicit Explicit

Automatic Controlled

Low effort High effort

Rapid Slow

High capacity Low capacity

Default process Inhibitory

Holistic, perceptual Analytic, reflective

Cluster 2 (Evolution

Evolutionary old Evolutionary recent

Evolutionary rationality Individual rationality

Shared with animals Uniquely human

Nonverbal Linked to language

Modular cognition Fluid intelligence

Cluster 3 (Functional characteristics)

Associative Rule based

Domain specific Domain General

References System 1 System 2

Fodor (1983, 2001) Input modules Highercognition

Schneider &Schiffrin (1977) Automatic Controlled

Epstein (1994), Epstein&Pacini (1999) Experiential Rational

Chaiken (1980), Chen &Chaiken (1999) Heuristic Systematic

Reber (1993), Evand& Over (1996) Implicit/tacit Explicit

Evans (1989, 2006) Heuristic Analytic

Sloman (1996), Smith &DeCoster (2000) Associative RuleBased

Hammond (1996) Intuitive Analytic

Stanovich (1999, 2004) System 1 (TASS) System 2 (Analytic)

Nisbett et al. (2001) Holistic Analytic

Wilson (2002) Adaptiveunconcious Concious

Lieberman (2003) Reflexive Reflective

Toates (2006) Stimulus bound Higher order

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34 P.A.C. Hoeks Contextualized Abstract Pragmatic Logical Parallel Sequential Stereotypical Egalitarian

Cluster 4 (Individual differences)

Universal Heritable

Independent of general intelligence Linked to general intelligence

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Appendix B: Online Questionnaire

Q1 Welcome and thank you for taking part in our research! Dear student, This study

contains questions that are related to your personality and we kindly ask you to read them carefully and answer all of them, as honestly as possible. Please bear in mind that there are no right or wrong answers and that your identity will be treated confidentially and anonymously. To proceed with the actual questionnaire, please press the “>>” button!

Q2 Please answer first to the following demographic questions: What is your Student number?

Your Student Number is important for this research and it will not be disclosed to other parties; we will use the information only for the purpose of this research.

Q3 What is your SONA ID? Your SONA ID is important for this research and it will not be disclosed

to other parties; we will use the information only for the purpose of this research.

Q4 What is your e-mail address? Your e-mail address is important for this research and it will not be

disclosed to other parties; we will use the information only for the purpose of this research.

Q5 What is your age? Q6 What is your gender?

 Male (1)  Female (2)

Q7 What study program are you following? Q8 What is your nationality?

Q9 Here are a number of characteristics that may or may not apply to you. For example, do you

agree that you are someone who likes to spend time with others? Please indicate the extent to which you agree or disagree with that statement. I see Myself as Someone Who...

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The Influence of Cognitive Style States on Creativity: A Dual-Process Approach

Master Thesis

June 2015