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Differences in Creative Problem-Solving Preferences across Occupations

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Title: Differences in Creative Problem-Solving Preferences across Occupations
Language: English
Authors: Puccio, Gerard J., Miller, Blair, Acar, Selcuk
Source: Journal of Creative Behavior. Dec 2019 53(4):576-592.
Availability: Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Peer Reviewed: Y
Page Count: 17
Publication Date: 2019
Document Type: Journal Articles
Reports - Research
Descriptors: Creativity, Problem Solving, Preferences, Cognitive Processes, Career Choice, Correlation, Prediction, Finance Occupations, Creative Thinking, Occupations, Work Attitudes, Work Environment, Stress Variables, Labor Turnover, Job Satisfaction
DOI: 10.1002/jocb.241
ISSN: 0022-0175
Abstract: FourSight theory contends that individuals show preferences for the mental operations rooted in the creative process. The four fundamental preferences measured by FourSight are Clarifiers, Ideators, Developers, and Implementers. The present study examined the extent to which certain occupations reflect a proclivity for these four creative-process preferences. Guided by Holland's theory of vocational choice, hypothesized relationships were formulated for the link between FourSight theory and 17 occupations. For example, it was predicted that those who work in finance would show a significant bias toward the Clarifier preference. Of the 17 hypothesized relationships between FourSight and occupation, statistical analysis of the FourSight preferences for 20,784 individuals showed support for 12 predictions and partial support for two of the hypothesized relationships. These findings clearly demonstrate that particular occupations engage specific creative-process preferences. Future investigations might wish to examine the degree to which the interaction between work and creative-thinking preferences predicts creative performance, satisfaction, stress, and turnover.
Abstractor: As Provided
Entry Date: 2019
Accession Number: EJ1237902
Database: ERIC
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  Value: <anid>AN0140455840;3u701dec.19;2019Dec23.03:47;v2.2.500</anid> <title id="AN0140455840-1">Differences in Creative Problem‐Solving Preferences Across Occupations </title> <p>FourSight theory contends that individuals show preferences for the mental operations rooted in the creative process. The four fundamental preferences measured by FourSight are Clarifiers, Ideators, Developers, and Implementers. The present study examined the extent to which certain occupations reflect a proclivity for these four creative‐process preferences. Guided by Holland's theory of vocational choice, hypothesized relationships were formulated for the link between FourSight theory and 17 occupations. For example, it was predicted that those who work in finance would show a significant bias toward the Clarifier preference. Of the 17 hypothesized relationships between FourSight and occupation, statistical analysis of the FourSight preferences for 20,784 individuals showed support for 12 predictions and partial support for two of the hypothesized relationships. These findings clearly demonstrate that particular occupations engage specific creative‐process preferences. Future investigations might wish to examine the degree to which the interaction between work and creative‐thinking preferences predicts creative performance, satisfaction, stress, and turnover.</p> <p>Keywords: Creative Problem Solving; person‐environment fit; FourSight; Holland's theory of occupational choice; cognitive style</p> <p>Originally developed by Alex Osborn ([<reflink idref="bib16" id="ref1">16</reflink>]), Creative Problem Solving (CPS) is an applied creativity model that provides process steps and cognitive strategies that enable individuals, teams, and organizations to more effectively respond to open‐ended challenges. As an applied creativity process, CPS is designed to deliver original and transformative responses to situations that are novel, ambiguous, and ill‐defined (Mumford, Zaccaro, Harding, Jacobs & Fleishman, [<reflink idref="bib14" id="ref2">14</reflink>]). Since its introduction more than 60 years ago, CPS has undergone continuous development to refine the model (Puccio, Murdock & Mance, [<reflink idref="bib29" id="ref3">29</reflink>]) and research into its efficacy has consistently demonstrated the value of this applied creativity process (Parnes & Meadow, [<reflink idref="bib18" id="ref4">18</reflink>]; Parnes & Noller, [<reflink idref="bib19" id="ref5">19</reflink>]; Puccio, Firestien, Coyle & Masucci, [<reflink idref="bib25" id="ref6">25</reflink>]). Indeed, as a result of their meta‐analytic review of creativity programs, Scott, Leritz and Mumford ([<reflink idref="bib36" id="ref7">36</reflink>]) concluded that CPS was one of the most effective creativity‐training programs.</p> <p>In the late 1990's, Puccio ([<reflink idref="bib22" id="ref8">22</reflink>]) asserted that CPS could be viewed as a set of mental operations. Furthermore, he predicted, as a result of cognitive styles, individuals were likely to express different degrees of preference for the mental operations associated with each step of this creativity process. Using the CPS framework as a starting point, he identified and tested self‐report items designed to assess thinking preferences conceptually linked to each step of the process. Factor analysis of these items revealed four distinct creative‐process preferences: Clarifier, Ideator, Developer, and Implementer (Puccio, [<reflink idref="bib23" id="ref9">23</reflink>]).</p> <p> <emph>Clarifiers</emph> prefer to identify the root cause of a problem, search for background information, collect data, give attention to details, and examine the situation from multiple perspectives. They are usually focused, methodical, orderly, and organized. They can be most helpful when they have access to information, receive clear direction, and are presented with the facts. At times, Clarifiers can be overly realistic and analytical.</p> <p> <emph>Ideators</emph> enjoy using their imaginations to generate many ideas. They introduce unusual and sometimes radical solutions by approaching challenges in more abstract and conceptual ways. As visionary and idealistic people, they like to focus on the big picture. Ideators tend to be playful, imaginative, flexible, and independent. They benefit from constant stimulation and are open to new experiences. Ideators can adapt to change quickly but may give too much credit to originality and off‐the‐wall solutions.</p> <p> <emph>Developers</emph> are inclined to refine and improve existing ideas, solutions or products. They do this by evaluating different possibilities and comparing the advantages and disadvantages of potential solutions. Developers can be described as being planful, pragmatic, structured, and reflective. They need time and space to consider and evaluate options before reaching a decision or conclusion. Their tendency toward perfection serves as a potential creativity barrier for Developers.</p> <p> <emph>Implementers</emph> possess an inclination toward action. They prefer to reach conclusions quickly and then to move forward as expeditiously as possible. They are driven to manifest their creative ideas. Implementers are persistent, decisive, determined, and assertive. They can be impulsive and may sometimes act prematurely. For further descriptions of these four creative‐thinking preferences, see Puccio, Mance, and Murdock ([<reflink idref="bib28" id="ref10">28</reflink>]) or Grivas and Puccio ([<reflink idref="bib8" id="ref11">8</reflink>]).</p> <p>The self‐report measure used to identify individuals' proclivity for each of these creative problem‐solving preferences is called FourSight (Puccio, [<reflink idref="bib23" id="ref12">23</reflink>]). Research studies utilizing the FourSight measure have consistently revealed sound psychometric properties and have provided initial insights into the robustness of this theory. For example, research into the FourSight scales has demonstrated how these creative‐thinking preferences respond in characteristically different ways to creativity training (Puccio, Wheeler & Cassandro, [<reflink idref="bib32" id="ref13">32</reflink>]), align with particular personality traits (Campos, Rubio, Atondo & Chorres, [<reflink idref="bib2" id="ref14">2</reflink>]; Puccio & Grivas, [<reflink idref="bib26" id="ref15">26</reflink>]), relate to entrepreneurial behavior (Campos et al., [<reflink idref="bib2" id="ref16">2</reflink>]), predict susceptibility to attention deficit hyperactivity disorder (White & Shah, [<reflink idref="bib40" id="ref17">40</reflink>]), and provide insight into knowledge management (Chan, [<reflink idref="bib4" id="ref18">4</reflink>]). The present study was designed to add to the expanding understanding of the implications of the creative problem‐solving preferences associated with the FourSight theory.</p> <p>In recent years, a clear trend has emerged in which creativity and creativity‐related skills are frequently cited among the most important 21st century workplace skills (Puccio, Keller Mathers, Acar & Cayirdag, [<reflink idref="bib27" id="ref19">27</reflink>]). And recently, a Bloomberg/BusinessWeek survey of hiring managers specifically identified creative problem‐solving as one of the skills most desired by employers (Otani, [<reflink idref="bib17" id="ref20">17</reflink>]). With the ubiquitous demand for creativity in today's jobs, the purpose of the present study was to explore whether creative problem‐solving preferences, as measured by FourSight, are uniformly present across different occupations or if different occupations reflect particular modes of thinking within the creative process.</p> <p>At a broad level, we predict that different occupations are likely to demand different aspects of the creative process and thus will attract individuals whose cognitive style preferences align with the kind of thinking emphasized in that particular occupation. Vocational choice research is not new; however, with the notable exception of Kirton's ([<reflink idref="bib12" id="ref21">12</reflink>]) Adaptor‐Innovator theory little research has examined occupational choice relative to creativity styles. Holland's ([<reflink idref="bib9" id="ref22">9</reflink>]) theory of occupational choice is one of the most well known models in the field of vocational psychology. The three basic premises of his theory provide a foundation to our predication that different creative problem‐solving preferences are likely to emerge in different occupations. First, Holland suggested that individuals can be characterized according to their personality type. To that end, Holland identified six personality types: Realistic (R), Investigative (I), Social (S), Conventional (C), Enterprising (E), and Artistic (A). Second, environments in which people work can be categorized in terms of the same personality types identified in the first premise. Third, a match between individual personality types and environment will influence vocational choice, achievement, and creative performance. Holland suggested that individuals select environments that enable them to fully use their skills and abilities, and reflect their values. More germane to the present study and associated predications, it has been argued that individuals seek out and select work environments that are compatible with their personality types, and avoid environments they believe are not conducive to their predispositions and values. To further reinforce homogeneity in personality type in a particular environment, those whose personality and preferences do not fit a particular work environment are likely to leave (Schneider, [<reflink idref="bib34" id="ref23">34</reflink>]). This is generally known as person–environment fit (Caplan, [<reflink idref="bib3" id="ref24">3</reflink>]; Moos, [<reflink idref="bib13" id="ref25">13</reflink>]; Pervin, [<reflink idref="bib20" id="ref26">20</reflink>]).</p> <p>We believe the same person–environment selection process would apply to FourSight theory. That is, individuals possess specific preferences for the mental operations within the creative process, and occupations are likely to vary in regard to which creative‐thinking operations are demanded as a result of the kinds of tasks found in those jobs. Therefore, individuals are likely to either implicitly or explicitly seek out those occupations that align with their creative‐process preferences. In a world that places a high demand on creativity, where it is now argued that creativity is required in all jobs (Trilling & Fadel, [<reflink idref="bib38" id="ref27">38</reflink>]), the present study was designed to examine the degree to which different jobs demand different mental operations within the creative process. Insights gained through such an investigation can promote a more refined discussion relative to the demands of the 21st century workplace. Rather than generic references to creativity and creative problem‐solving as 21st century skills, should links between FourSight preferences and specific occupations exist, then the conversation might evolve from vague references to creative thinking as a workplace skill to one focused on the specific forms of creative thinking required by different jobs.</p> <p>Creativity represents a complex form of thinking. Indeed, the updated version of Bloom's taxonomy, which arrays human thought from the simplest forms to the most complex, placed creativity at the highest level of human cognition (Anderson & Krathwohl, [<reflink idref="bib1" id="ref28">1</reflink>]). This taxonomy purports that the more complex forms of thought, such as creativity, must innately subsume a range of more specific ways of thinking. Commensurate with the view that creative thinking is a complex form of thought, the present study set out to determine how the four styles or components of creative thought, as measured by FourSight, wax and wane depending on the occupation.</p> <p>Recent research reflects the potential interaction between work environments and FourSight preferences. Puccio and Acar ([<reflink idref="bib24" id="ref29">24</reflink>]) analyzed the FourSight preferences of more than 7,000 individuals and found that those in strategic‐level leadership positions possessed significantly different creative problem‐solving preferences than those in lower‐level leadership positions. Specifically, senior leaders showed significantly higher preferences for the Ideator and Implementer components of the creative process. The visionary, flexible, and original thought processes associated with the Ideator tendency in particular seem to align well with the demands that an increasingly complex and fluid work environment makes on organizational leaders.</p> <p>While Puccio and Acar's ([<reflink idref="bib24" id="ref30">24</reflink>]) study provides initial insights into the dynamics of FourSight theory within organizational contexts, FourSight theory is grounded in the creativity literature and not in vocational psychology. Therefore, to guide the formulation of hypotheses that link FourSight preferences to specific occupations we turned to Holland's theory. To that end, we began by examining the conceptual relationships between Holland's personality types and the personality characteristics associated with Clarifiers, Ideators, Developers, and Implementers (Puccio & Grivas, [<reflink idref="bib26" id="ref31">26</reflink>]; Puccio & Schwagler, [<reflink idref="bib30" id="ref32">30</reflink>]; Rife, [<reflink idref="bib33" id="ref33">33</reflink>]). Based on the characteristics associated with the respective styles measured by both theories, Table  shows the predicted intersection between the FourSight preferences and Holland's personality types. Descriptions of the FourSight preferences and Holland's personality types seemed to reveal clear conceptual connections (see X's in Table ). In FourSight, the Integrator style reflects an individual who does not show strong preference for one or more of the four main creative‐process preferences described earlier. Such individuals are said to show fluidity across the four basic operations associated with creative problem solving. Additionally, Integrators are much more likely to express a concern for relationships and group harmony.</p> <p>Conceptual Connections between FourSight Preferences and Holland's Personality Types</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left" /><th align="left">FourSight Scales</th></tr><tr><th align="left" /><th align="left">Clarifier</th><th align="left">Ideator</th><th align="left">Developer</th><th align="left">Implementer</th><th align="left">Integrator</th></tr><tr><th align="left">Holland personality types</th><th align="left">(Focused on facts, detail oriented, orderly)</th><th align="left">(Focused on big picture, imaginative, flexible)</th><th align="left">(Focused on continuous progress, discerning, pragmatic)</th><th align="left">(Focused on action, determined, assertive)</th><th align="left">(Focused on relationships, inclusive, steady)</th></tr></thead><tbody><tr><td align="left">Realistic(No‐nonsense, practical, likes mechanical things)</td><td align="left">X</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left">Conventional(Organized, detail oriented, likes numbers and records)</td><td align="left">X</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left">Artistic(Original, expressive, dislikes repetitive activities)</td><td align="left" /><td align="left">X</td><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left">Investigative(Methodical, experiments, likes solving problems)</td><td align="left" /><td align="left" /><td align="left">X</td><td align="left" /><td align="left" /></tr><tr><td align="left">Enterprising(Energetic, persuasive, dislikes analytical thinking)</td><td align="left" /><td align="left" /><td align="left" /><td align="left">X</td><td align="left" /></tr><tr><td align="left">Social(Cooperative, empathetic, likes helping people)</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left">X</td></tr></tbody></table> </ephtml> </p> <p>After establishing the conceptual relationships between FourSight theory and Holland's personality types, we then formulated hypotheses in regard to the creative problem‐solving preference most likely to be prevalent within particular occupations and professions. When individuals complete FourSight online, they are asked to voluntarily identify their occupation or profession. Respondents choose from among 17 different occupations and professions. Formulation of our hypotheses resulted from a two‐step process. First, we identified the Holland personality type most widely associated with each of the occupations and professions in our data set (see Table  for the Holland codes associated with each occupation). The methodology used to code the 17 occupations in light of Holland's six personality types is summarized in the Method section. Second, we then referred to the predicted intersection between Holland's theory and FourSight to hypothesize which of the creative problem‐solving preferences would be most dominant in that occupation or profession. For example, quality and operations were linked to the Realistic type. Since there was a conceptual link between Realistic and the FourSight Clarifier preference (see Table ), we hypothesized that quality and operations would show Clarifier as their most clear creative‐process preference. In contrast, advertising is linked to Holland's Artistic type, which in turn seems to be most closely associated with FourSight Ideators. Thus, we hypothesized that those who selected advertising as their profession were more likely to show a strong tendency toward the Ideator preference. All 17 hypothesized relationships between FourSight and occupation are found in Table .</p> <p>Descriptive Values of Occupations Along with Associated Holland Categories and Hypothesized FourSight Styles</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left">Occupations (Holland Code)</th><th align="left"><italic>n</italic></th><th align="left">Hypothesized FourSight style</th><th align="left">Result</th><th align="left">Clarifier</th><th align="left">Ideator</th><th align="left">Developer</th><th align="left">Implementer<xref ref-type="fn" rid="tfn2" /></th></tr><tr><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th></tr></thead><tbody><tr><td align="left">Finance (C)</td><td align="left">1,959</td><td align="left">H1‐Clarifier</td><td align="left">Supported<xref ref-type="fn" rid="tfn3" /></td><td align="left">35.10</td><td align="left">4.99</td><td align="left">32.17</td><td align="left">6.31</td><td align="left">33.26</td><td align="left">5.76</td><td align="left">31.14</td><td align="left">5.18</td></tr><tr><td align="left">Quality (R)</td><td align="left">319</td><td align="left">H2‐Clarifier</td><td align="left">Supported</td><td align="left">35.62</td><td align="left">5.02</td><td align="left">31.60</td><td align="left">6.43</td><td align="left">33.01</td><td align="left">5.73</td><td align="left">31.21</td><td align="left">5.13</td></tr><tr><td align="left">Operations (R)</td><td align="left">1,621</td><td align="left">H3‐Clarifier</td><td align="left">Partially<xref ref-type="fn" rid="tfn4" /></td><td align="left">34.89</td><td align="left">5.43</td><td align="left">33.01</td><td align="left">6.25</td><td align="left">32.96</td><td align="left">6.15</td><td align="left">32.11</td><td align="left">5.05</td></tr><tr><td align="left">Marketing (A)</td><td align="left">2,362</td><td align="left">H4‐Ideator</td><td align="left">Supported</td><td align="left">34.41</td><td align="left">5.40</td><td align="left">34.33</td><td align="left">6.08</td><td align="left">32.64</td><td align="left">5.80</td><td align="left">31.81</td><td align="left">5.02</td></tr><tr><td align="left">Consulting (I)</td><td align="left">778</td><td align="left">H5‐Ideator</td><td align="left">Supported</td><td align="left">35.06</td><td align="left">5.93</td><td align="left">35.28</td><td align="left">6.24</td><td align="left">33.40</td><td align="left">5.97</td><td align="left">31.40</td><td align="left">5.48</td></tr><tr><td align="left">Advertising (A)</td><td align="left">439</td><td align="left">H6‐Ideator</td><td align="left">Supported</td><td align="left">35.09</td><td align="left">4.96</td><td align="left">34.79</td><td align="left">5.83</td><td align="left">32.50</td><td align="left">5.55</td><td align="left">31.00</td><td align="left">5.68</td></tr><tr><td align="left">Design (A)</td><td align="left">467</td><td align="left">H7‐Ideator</td><td align="left">Supported</td><td align="left">34.97</td><td align="left">5.83</td><td align="left">35.51</td><td align="left">6.00</td><td align="left">34.01</td><td align="left">6.07</td><td align="left">32.28</td><td align="left">5.35</td></tr><tr><td align="left">IT (I)</td><td align="left">1,641</td><td align="left">H8‐Developer</td><td align="left">Supported</td><td align="left">35.52</td><td align="left">5.21</td><td align="left">33.63</td><td align="left">6.25</td><td align="left">34.04</td><td align="left">5.77</td><td align="left">32.08</td><td align="left">5.01</td></tr><tr><td align="left">Engineering (I)</td><td align="left">2,435</td><td align="left">H9‐Developer</td><td align="left">Supported</td><td align="left">35.10</td><td align="left">5.02</td><td align="left">32.79</td><td align="left">6.15</td><td align="left">33.87</td><td align="left">5.47</td><td align="left">31.83</td><td align="left">4.78</td></tr><tr><td align="left">R&D (I)</td><td align="left">1,855</td><td align="left">H10‐Developer</td><td align="left">Partially</td><td align="left">35.16</td><td align="left">5.47</td><td align="left">34.16</td><td align="left">6.62</td><td align="left">33.46</td><td align="left">5.98</td><td align="left">31.74</td><td align="left">5.22</td></tr><tr><td align="left">Higher education (I)</td><td align="left">2,085</td><td align="left">H11‐Developer</td><td align="left">Not supported<xref ref-type="fn" rid="tfn4" /></td><td align="left">34.34</td><td align="left">5.74</td><td align="left">35.35</td><td align="left">6.16</td><td align="left">33.13</td><td align="left">6.13</td><td align="left">31.64</td><td align="left">5.54</td></tr><tr><td align="left">Sales (E)</td><td align="left">1,684</td><td align="left">H12‐Implementer</td><td align="left">Supported</td><td align="left">34.57</td><td align="left">5.39</td><td align="left">33.39</td><td align="left">5.94</td><td align="left">32.55</td><td align="left">6.07</td><td align="left">32.07</td><td align="left">4.67</td></tr><tr><td align="left">Human Resources (E)</td><td align="left">1,089</td><td align="left">H13‐Implementer</td><td align="left">Supported</td><td align="left">33.75</td><td align="left">5.44</td><td align="left">33.04</td><td align="left">6.61</td><td align="left">32.13</td><td align="left">6.00</td><td align="left">31.42</td><td align="left">5.20</td></tr><tr><td align="left">Communication/PR (E)</td><td align="left">388</td><td align="left">H14‐Implementer</td><td align="left">Partially</td><td align="left">34.05</td><td align="left">5.87</td><td align="left">34.52</td><td align="left">5.92</td><td align="left">32.07</td><td align="left">6.05</td><td align="left">32.03</td><td align="left">5.07</td></tr><tr><td align="left">Purchasing (E)</td><td align="left">295</td><td align="left">H15‐Implementer</td><td align="left">Supported</td><td align="left">34.63</td><td align="left">5.34</td><td align="left">31.99</td><td align="left">6.59</td><td align="left">32.76</td><td align="left">5.99</td><td align="left">32.16</td><td align="left">4.98</td></tr><tr><td align="left">K‐12 Education (S)</td><td align="left">890</td><td align="left">H16‐Integrator</td><td align="left">Not supported</td><td align="left">33.85</td><td align="left">5.58</td><td align="left">32.53</td><td align="left">6.72</td><td align="left">32.22</td><td align="left">6.48</td><td align="left">31.50</td><td align="left">5.28</td></tr><tr><td align="left">Social Services (S)</td><td align="left">477</td><td align="left">H17‐Integrator</td><td align="left">Supported</td><td align="left">34.36</td><td align="left">5.77</td><td align="left">33.96</td><td align="left">5.89</td><td align="left">33.03</td><td align="left">6.07</td><td align="left">31.49</td><td align="left">5.59</td></tr><tr><td align="left">Total</td><td align="left">20,784</td><td align="left" /><td align="left" /><td align="left">34.76</td><td align="left">5.41</td><td align="left">33.65</td><td align="left">6.33</td><td align="left">33.11</td><td align="left">5.95</td><td align="left">31.73</td><td align="left">5.14</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Notes</emph>. HR = Human resources; IT = Information technology; R&D = Research and development; PR = Public relations.</p> <ulist> <item>2 Implementer scores are based on eight items, whereas remaining three scales are based on nine items.</item> <item>3 Hypothesis supported if anticipated preference significantly higher than remaining scales or if hypothesized preference was highest score between two preferences that were significantly higher than the rest.</item> <item>4 Hypothesis partially supported if hypothesized scale was among two or more scales that were significantly higher than remaining scales, but the hypothesized scale did not have the highest score among these scales.</item> <item>5 Hypothesis not supported if hypothesized preference was not among scales that were significantly higher than remaining scales.</item> </ulist> <p>In summary, Schneider ([<reflink idref="bib34" id="ref34">34</reflink>],[<reflink idref="bib35" id="ref35">35</reflink>]) argued that people are attracted to, and selected by, work environments that match their personality characteristics, and that attrition will occur among those whose personalities do not match. Applying Schneider's attraction–selection–attrition model to occupational choice, we anticipated that the mental processes associated with occupations would attract and retain individuals with particular FourSight preferences. Furthermore, given the range of different occupations in the present study, as highlighted by the hypotheses in Table , we anticipated that different creative‐thinking preferences would align with particular occupations.</p> <p>For all hypotheses but one, Holland's theory was used to predict the relationship between occupation and creative‐process preferences. According to the Dictionary of Holland Occupational Codes, consulting is most closely associated with Holland's Investigative type. The Investigative type seems to align with FourSight's Developer preference (see Table ); however, the research team hypothesized that consulting would show a tendency toward the Ideator preference. Consulting is a broad category. Given the fact that FourSight has been widely used with creativity trainers and consultants, individuals who are asked by organizations to facilitate ideas and to provide novel perspectives, we concluded that the Ideator preference seemed to be a better fit for those who identified themselves as consultants in the present data set.</p> <p>We know creativity is in high demand in the 21<sups>st</sups> century workplace. We also know that while creative thinking is applicable to all occupations, it must be recognized that creative thinking is complex. With this in mind, the present study sought to understand the degree to which occupations vary in regard to the particular aspect of creative thinking they demand (i.e., clarifying, ideating, developing, and implementing). Specifically, we predicted that different occupations would emphasize different thinking preferences within the creative process. Following the standard implications associated with person–environment theory, it could then be argued that individuals' performance, stress, and satisfaction at work could be predicted by the degree of fit between their creative‐process preferences and the particular creative‐thinking operations favored by their work. However, before such dynamics can be studied, it is necessary to first establish whether different occupations reflect different preferences along the creative process. The present investigation represents an important first step in this line of research.</p> <hd id="AN0140455840-2">Method</hd> <p></p> <hd id="AN0140455840-3">Participants</hd> <p>The study consisted of 20,784 participants. Mean age was 40.26 (<emph>SD</emph> = 9.97). Only a small proportion of the participants (17.5%) reported gender and among those reported, males (57.8%) were higher than females (42.2%). Participants were mostly from the private sector (83.3%) followed by the field of education (14.3%), and others including social services, government, and healthcare (2.4%). The sample was also representative of various organizational levels such as non‐management (3.8%), supervisor or department head (11.7%), middle management (21.4%), director (12.8%), vice president (5.6%), and executive (4.9%).</p> <hd id="AN0140455840-4">Instruments</hd> <p></p> <hd id="AN0140455840-5">FourSight</hd> <p>Consisting of 36 self‐report items, FourSight version 6.1 measures four different preferences of problem solving: Clarifier, Ideator, Developer, and Implementer. Each of these four preferences is measured by nine items (Puccio, [<reflink idref="bib23" id="ref36">23</reflink>]). Respondents used a five‐point Likert scale (1 =  Not like me at all, 2 =  Not much like me, 3 =  Like me, 4 =  Very much like me, 5 =  Always like me). All four scales had good internal reliability (α > .78; Puccio & Acar, [<reflink idref="bib24" id="ref37">24</reflink>]) and construct validity evidence was reported in previous research (Puccio, [<reflink idref="bib22" id="ref38">22</reflink>], [<reflink idref="bib23" id="ref39">23</reflink>]).</p> <p>FourSight generates an individual profile of problem‐solving preference as a combination of the four preferences. The Clarifier preference is measured through such items as "I like taking the time to clarify the exact nature of the problem." A sample Ideator item is "I enjoy coming up with unique ways of looking at a problem." The following statement represents an item used to identify the Developer preference: "I like to generate criteria that can be used to identify the best options." A sample Implementer item is "I enjoy putting ideas into action."</p> <hd id="AN0140455840-6">Procedures</hd> <p>After completing the FourSight measure online, participants were presented with a demographic form and asked to voluntarily respond to the options contained in this form. The personal information form includes questions about their age, gender, positions at their respective organization, sector, and their occupation.</p> <p>Participants were asked to select from 17 different major occupations: sales, marketing, operations, human resources, communication/public relations, purchasing, information technology, quality, finance, engineering, consulting, advertising, research and development, design, higher education, K‐12 education, and social services. The first set of analyses focused on the four FourSight scores (i.e., Clarifier, Ideator, Developer, Implementer) for each of the 17 occupations. Because these repeated measures analyses used four FourSight scales as the dependent variables, mean values were converted into <emph>z</emph>‐scores to prevent minor scale differences that might mask meaningful discrepancies among the four scales. Repeated measures analyses used these <emph>z</emph>‐scores as the dependent variables.</p> <p>The second cycle of analyses relied on categories that we developed based on Holland's ([<reflink idref="bib9" id="ref40">9</reflink>]) theory of occupations. Again, Holland's theory consisted of six types: Realistic (R), Artistic (A), Investigative (I), Social (S), Enterprising (E), and Conventional (C). Holland approached occupations as combinations of these six types. To that end, the Dictionary of Holland Occupational Codes (Gottfredson & Holland, [<reflink idref="bib7" id="ref41">7</reflink>]) and O*Net OnLine ("Preferences for work environments and outcomes," [<reflink idref="bib21" id="ref42">21</reflink>]) resources provided extensive lists of occupations along with corresponding Holland personality type. These sources associated occupations with three different personality types, the first being the most dominant. In some cases, there were multiple variations of the same occupation. For this study, we either selected the most dominant or repeating style across different varieties. For example, there were approximately 180 different variations of sales (e.g., salesperson, sales representative) and all had Enterprising (E) as the most dominant category (Gottfredson & Holland, [<reflink idref="bib7" id="ref43">7</reflink>]). Similarly, a clear dominant Holland category was found for purchasing (E), communication/PR (E), operations (R), quality (R), higher education (I), research and development (I), social services (S), and K‐12 education (S). In some cases, these sources did not provide a clear style, as was the case for advertising, finance, design, information technology, human resources, marketing, consulting, and engineering. In such instances, the research team discussed the best style fit based on the description of each style and the skills required for the respective occupation. As a means of verification, the corresponding FourSight style was taken into consideration (see Table ). For example, financial planner was coded as ESC (Enterprising, Social, Conventional) and teller (Financial) as CSE (Conventional, Enterprising, Social). We linked finance to Conventional because it "requires clerical or skills required in meeting precise standards for performance...concern for orderliness and routines...working with things, numbers, or machines" (Gottfredson & Holland, [<reflink idref="bib7" id="ref44">7</reflink>], p. 5) and this description conceptually aligns with the FourSight Clarifier preference which we associated with Holland's Conventional type. The authors used this methodology to reach consensus for the Holland code assigned to each of the remaining occupations. Table  presents the 17 occupations along with the associated Holland category and hypothesized FourSight style.</p> <hd id="AN0140455840-7">Results</hd> <p>FourSight was the central focus of the analyses; therefore, preliminary investigation was on the internal reliability of its subscales. Internal reliabilities were.79 for Clarifier,.81 for Ideator,.81 for Developer, and.73 for Implementer. Alpha was.80 when item 36 was removed from the Implementer scale. The analyses used this eight‐item version of the Implementer scale.</p> <hd id="AN0140455840-8">Comparisons Across Foursight Scores within Occupations</hd> <p>The present analyses compared Clarifier, Ideator, Developer, and Implementer scores for each individual occupation. The repeated measures analyses are sensitive to scale differences and therefore analyses used <emph>z</emph>‐scores rather than raw scores. Each repeated measures analysis used four <emph>z</emph>‐scores as the dependent variable. As a result, means reported for each individual analysis were different from those shown in Table . We repeated this for all 17 occupations. Because the assumption of sphericity was often violated, we reported the univariate <emph>F</emph> test results using lower bound adjustment (Geisser & Greenhouse, [<reflink idref="bib6" id="ref45">6</reflink>]). Lower bound adjustment is known as a conservative test of hypothesis (Huberty & Olejnik, [<reflink idref="bib10" id="ref46">10</reflink>]). Decisions regarding the degree to which this analysis provided support for the hypotheses related to the four creative‐thinking preferences adhered to the rubric found at the bottom of Table .</p> <p>As seen in Table , we hypothesized that finance (H1), quality (H2), and operations (H3) were associated with the Clarifier preference. Repeated measures analyses indicated that people in finance had significantly <emph>F</emph>(<reflink idref="bib1" id="ref47">1</reflink>, 1958) = 69.33, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0001" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .034) higher Clarifier scores (<emph>M </emph>=<emph> </emph>0.11, <emph>SD</emph> = 0.92) than Developer (<emph>M </emph>=<emph> </emph>0.06, <emph>SD</emph> = 0.97), Implementer (<emph>M </emph>=<emph> </emph>−0.07, <emph>SD</emph> = 1.01), and Ideator scores (<emph>M </emph>=<emph> </emph>−0.18, <emph>SD</emph> = 1.01). Figure  displays the FourSight scores for finance. The same analysis was repeated for those who work at quality control units. Clarifier scores (<emph>M </emph>=<emph> </emph>0.21, <emph>SD</emph> = 0.92) were significantly higher <emph>F</emph>(<reflink idref="bib1" id="ref48">1</reflink>, 318) = 23.86, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0002" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .07) than Developer (<emph>M </emph>=<emph> </emph>0.02, <emph>SD</emph> = 0.96), Implementer (<emph>M </emph>=<emph> </emph>−0.06, <emph>SD</emph> = 1.00), and Ideator scores (<emph>M </emph>=<emph> </emph>‐.27, <emph>SD</emph> = 1.03). Those who work in operations tend to demonstrate significantly, <emph>F</emph>(<reflink idref="bib1" id="ref49">1</reflink>, 1620) = 18.11, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0003" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .011, stronger preference for the Implementer style (<emph>M </emph>=<emph> </emph>0.12, <emph>SD</emph> = 0.98) followed by Clarifier style (<emph>M </emph>=<emph> </emph>0.07, <emph>SD</emph> = 1.00) than Developer styles (<emph>M </emph>=<emph> </emph>0.01, <emph>SD</emph> = 1.03) and Ideator (<emph>M </emph>=<emph> </emph>−0.05, <emph>SD</emph> = 1.00). Pairwise comparisons indicated that the difference between Clarifier and Implementer scores was not significant whereas Clarifier and Implementer scores were significantly higher than both Ideator and Developer scores. Analyses supported two of the hypotheses related to finance and quality; operations was partially supported. See Table  for a summary of the degree to which the respective hypotheses within the Clarifier set of preferences were supported, and for the analyses of the hypotheses to follow.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/3U7/01dec19/jocb241-fig-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jocb241-fig-0001.jpg" title="FourSight scores for Finance." /> </p> <p></p> <p>We expected those in marketing (H4), consulting (H5), advertising (H6), and design (H7) to demonstrate stronger preferences for ideation. Among those in marketing, Ideator scores (<emph>M </emph>=<emph> </emph>0.16, <emph>SD</emph> = 0.97) were significantly higher, <emph>F</emph>(<reflink idref="bib1" id="ref50">1</reflink>, 2361) = 33.43, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0004" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .014, than Implementer (<emph>M </emph>=<emph> </emph>0.06, <emph>SD</emph> =0.98), Clarifier (<emph>M </emph>=<emph> </emph>−0.02, <emph>SD</emph> =0.99), and Developer scores (<emph>M </emph>=<emph> </emph>−0.04, <emph>SD</emph> =0.97). Figure  illustrates the FourSight scores for marketing. When the four scores are compared for consulting, Ideator scores (<emph>M </emph>=<emph> </emph>0.31, <emph>SD</emph> = 1.00) were significantly higher, <emph>F</emph>(<reflink idref="bib1" id="ref51">1</reflink>, 777) = 21.77, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0005" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .027 than Clarifier (<emph>M </emph>=<emph> </emph>0.10, <emph>SD</emph> = 1.09), Developer (<emph>M </emph>=<emph> </emph>0.08, <emph>SD</emph> = 1.00), and Implementer scores (<emph>M </emph>=<emph> </emph>−0.02, <emph>SD</emph> = 1.06). In advertising, Ideator scores (<emph>M </emph>=<emph> </emph>0.24, <emph>SD</emph> = 0.93) were again significantly higher, <emph>F</emph>(<reflink idref="bib1" id="ref52">1</reflink>, 438) = 16.54, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0006" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .036, than Clarifier (<emph>M </emph>=<emph> </emph>0.11, <emph>SD</emph> = 0.91), Developer (<emph>M </emph>=<emph> </emph>−0.07, <emph>SD</emph> = 0.93), and Implementer scores (<emph>M </emph>=<emph> </emph>−0.10, <emph>SD</emph> = 1.10). Similarly, those in design also had significantly, <emph>F</emph>(<reflink idref="bib1" id="ref53">1</reflink>, 466) = 10.89, <emph>p </emph>=<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0007" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .023, higher Ideator scores (<emph>M </emph>=<emph> </emph>0.35, <emph>SD</emph> = 0.96) than Developer (<emph>M </emph>=<emph> </emph>0.19, <emph>SD</emph> = 1.02), Implementer (<emph>M </emph>=<emph> </emph>0.15, <emph>SD</emph> = 1.04), and Clarifier scores (<emph>M </emph>=<emph> </emph>0.09, <emph>SD</emph> = 1.07). The results supported all four hypotheses concerning the Ideator style (H4, H5, H6, H7).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/3U7/01dec19/jocb241-fig-0002.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jocb241-fig-0002.jpg" title="FourSight scores for Marketing." /> </p> <p></p> <p>We hypothesized that those in information technology (H8), engineering (H9), research and development (H10), and higher education (H11) would have significantly higher scores for the Developer scale. Analyses with those in information technology (IT) had significantly, <emph>F</emph>(<reflink idref="bib1" id="ref54">1</reflink>, 1640) = 15.43, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0008" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .009, higher Developer (<emph>M </emph>=<emph> </emph>0.19, <emph>SD</emph> = 0.97) and Clarifier scores (<emph>M </emph>=<emph> </emph>0.19, <emph>SD</emph> = 0.96) than Implementer (<emph>M </emph>=<emph> </emph>0.11, <emph>SD</emph> = 0.97) and Ideator scores (<emph>M </emph>=<emph> </emph>0.05, <emph>SD</emph> = 1.00) (see Figure ). The results for engineers showed a similar pattern with Developer (<emph>M </emph>=<emph> </emph>0.16, <emph>SD</emph> = 0.92) and Clarifier (<emph>M </emph>=<emph> </emph>0.11, <emph>SD</emph> = 0.97) scores being significantly higher, <emph>F</emph>(<reflink idref="bib1" id="ref55">1</reflink>, 2434) = 61.87, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0009" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .025, than Implementer (<emph>M </emph>=<emph> </emph>0.06, <emph>SD</emph> = 0.93) and Ideator scores (<emph>M </emph>=<emph> </emph>−0.08, <emph>SD</emph> = 0.97). In contrast to information technology, Developer and Clarifier scores were also significantly different from each other for engineers.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/3U7/01dec19/jocb241-fig-0003.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jocb241-fig-0003.jpg" title="FourSight scores for Information Technology (IT)." /> </p> <p></p> <p>Contrary to the hypotheses, analyses with those who work in research and development (R&D) had higher Ideator scores (<emph>M </emph>=<emph> </emph>0.14, <emph>SD</emph> = 1.06) than Clarifier (<emph>M </emph>=<emph> </emph>0.12, <emph>SD</emph> = 1.00), Developer (<emph>M </emph>=<emph> </emph>0.09, <emph>SD</emph> = 1.00), and Implementer scores (<emph>M </emph>=<emph> </emph>0.04, <emph>SD</emph> = 1.01) but the difference was significant only with the Implementer scores, <emph>F</emph>(<reflink idref="bib1" id="ref56">1</reflink>, 1854) = 5.00, <emph>p </emph><<emph> </emph>.025, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0010" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .003. Likewise, Ideator showed the highest score (<emph>M </emph>=<emph> </emph>0.33, <emph>SD</emph> = 0.99) among those in higher education and was significantly different, <emph>F</emph>(<reflink idref="bib1" id="ref57">1</reflink>, 2084) = 80.37, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0011" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .037, than Developer (<emph>M </emph>=<emph> </emph>0.04, <emph>SD</emph> = 1.03), Implementer (<emph>M </emph>=<emph> </emph>0.02, <emph>SD</emph> = 1.08), and Clarifier scores (<emph>M </emph>=<emph> </emph>−0.03, <emph>SD</emph> = 1.05). In summary, two Developer hypotheses were supported (IT and engineering), one was partially supported (R&D), and one was not supported (higher education).</p> <p>Lastly, we tested the hypotheses linking Implementer style to sales (H12), human resources (H13), communications/public relations (H14), and purchasing (H15). Concerning sales, Implementer scores (<emph>M </emph>=<emph> </emph>0.11, <emph>SD</emph> = 0.91) were significantly higher, <emph>F</emph>(<reflink idref="bib1" id="ref58">1</reflink>, 1683) = 16.64, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0012" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .010, than Ideator (<emph>M </emph>=<emph> </emph>0.01, <emph>SD</emph> = 0.95), Clarifier (<emph>M </emph>=<emph> </emph>0.01, <emph>SD</emph> = 0.99), and Developer scores (<emph>M </emph>=<emph> </emph>−0.06, <emph>SD</emph> = 1.02). Figure  shows the FourSight scores for sales. For human resources, significant differences were found across the four scales <emph>F</emph>(<reflink idref="bib1" id="ref59">1</reflink>, 1088) = 5.76, <emph>p </emph>=<emph> </emph>.017, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0013" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .005) with Implementer scores being the highest (<emph>M </emph>=<emph> </emph>−0.02, <emph>SD</emph> = 1.01) followed by Ideator (<emph>M </emph>=<emph> </emph>−0.04, <emph>SD</emph> = 1.06), Developer (<emph>M </emph>=<emph> </emph>−0.13, <emph>SD</emph> = 1.01), and Clarifier scores (<emph>M </emph>=<emph> </emph>−0.14, <emph>SD</emph> = 1.00). However, pairwise differences revealed that Implementer scores were significantly higher than Clarifier and Developer scores but not Ideator scores. Comparisons for those who work at communications/public relations (PR) indicated significantly higher, <emph>F</emph>(<reflink idref="bib1" id="ref60">1</reflink>, 387) = 14.63, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0014" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .036, Ideator (<emph>M </emph>=<emph> </emph>0.19, <emph>SD</emph> = 0.95) and Implementer scores (<emph>M </emph>=<emph> </emph>0.10, <emph>SD</emph> = 0.99) than Clarifier (<emph>M </emph>=<emph> </emph>−0.08, <emph>SD</emph> = 1.08) and Developer scores (<emph>M </emph>=<emph> </emph>−0.14, <emph>SD</emph> = 1.01). The difference between Ideator and Implementer scores was not significant. In purchasing, Implementer scores (<emph>M </emph>=<emph> </emph>0.12, <emph>SD</emph> = 0.97) were significantly higher, <emph>F</emph>(<reflink idref="bib1" id="ref61">1</reflink>, 294) = 12.57, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0015" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .041, than Developer (<emph>M </emph>=<emph> </emph>−0.02, <emph>SD</emph> = 1.00) and Ideator scores (<emph>M </emph>=<emph> </emph>−0.21, <emph>SD</emph> = 1.05) but not than Clarifier scores (<emph>M </emph>=<emph> </emph>0.02, <emph>SD</emph> = 0.97). The analyses relative to the Implementer hypotheses showed three predictions were supported (sales, human resources, and purchasing) and one was partially supported (communication/PR).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/3U7/01dec19/jocb241-fig-0004.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jocb241-fig-0004.jpg" title="FourSight scores for Sales." /> </p> <p></p> <p>We compared FourSight scores for K‐12 educators (H16) and social services (H17) expecting them to be relatively equal across all four scales; that is, showing no statistically significant differences among the four preferences. Implementer scores (<emph>M </emph>=<emph> </emph>−0.00, <emph>SD</emph> = 1.03) were significantly higher, <emph>F</emph>(<reflink idref="bib1" id="ref62">1</reflink>, 889) = 5.46, <emph>p </emph>=<emph> </emph>.020, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0016" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .006, among K‐12 educators than Developer (<emph>M </emph>=<emph> </emph>−0.12, <emph>SD</emph> = 1.09), Clarifier (<emph>M </emph>=<emph> </emph>−0.12, <emph>SD</emph> = 1.02), and Ideator scores (<emph>M </emph>=<emph> </emph>−0.13, <emph>SD</emph> = 1.08). For social services, Ideator scores (<emph>M </emph>=<emph> </emph>0.11, <emph>SD</emph> = 0.94) were highest but not significantly different from, <emph>F</emph>(<reflink idref="bib1" id="ref63">1</reflink>, 478) = 2.80, <emph>p </emph>=<emph> </emph>.10, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0017" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .006, Implementer (<emph>M </emph>=<emph> </emph>−0.01, <emph>SD</emph> = 1.09), Clarifier (<emph>M </emph>=<emph> </emph>−0.03, <emph>SD</emph> = 1.06), and Developer scores (<emph>M </emph>=<emph> </emph>0.02, <emph>SD</emph> = 1.02). With respect to the Integrator profile, one hypothesis was confirmed (social services) while the other was not (K‐12 education).</p> <hd id="AN0140455840-13">Comparison of Holland's Six Categories on FourSight Scores</hd> <p>To test the veracity of the conceptual links made between the Holland and FourSight theories, see Table , the next series of analyses compared Holland's six categories for each of the FourSight scores, respectively. All occupations related to each of the respective six Holland personality types were collapsed and four FourSight scales were compared across these six categories (Realistic=operations and quality; Artistic=marketing, advertising, and design; Investigative=information technology, engineering, research and development, and higher education; Social=K‐12 education and social services; Enterprising=sales, human resources, communication, human resources, and purchasing; Conventional=finance). We expected those in Conventional (<emph>n </emph>=<emph> </emph>1,940) and Realistic occupations (<emph>n </emph>=<emph> </emph>1,959) to have higher scores on the Clarifier scale, Artistic occupations (<emph>n </emph>=<emph> </emph>3,268) to have higher scores on the Ideator scale, Investigative occupations (<emph>n </emph>=<emph> </emph>8,016) to have higher scores on the Developer scale, and Enterprising occupations (<emph>n </emph>=<emph> </emph>3,456) to have higher scores on the Implementer scale.</p> <p>With respect to the Social personality type, it was not possible to use the present analysis to test the hypothesized link with the FourSight Integrator style. As stated previously, an Integrator style is reflective of an individual profile for which there are no significant differences across the four preferences (i.e., Clarifier, Ideator, Developer, and Implementer). Therefore, since there is no single score used to represent the Integrator style, it is not possible to collapse and compare the Social occupations for Integrator. However, it should be recalled that the previous analysis on specific occupations, namely K‐12 education and social services, did provide some insight into the connection between the Integrator style and Holland's Social personality type.</p> <p>First ANOVA compared the six Holland categories on Clarifier scale. Conventional had the highest score (<emph>M </emph>=<emph> </emph>35.10, <emph>SD</emph> = 4.99) followed by Realistic (<emph>M </emph>=<emph> </emph>35.01, <emph>SD</emph> = 5.37), and Investigative (<emph>M </emph>=<emph> </emph>35.00, <emph>SD</emph> = 5.37) which were significantly higher, <emph>F</emph>(<reflink idref="bib5" id="ref64">5</reflink>, 20006) = 17.51, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0018" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .004, than Artistic (<emph>M </emph>=<emph> </emph>34.58, <emph>SD</emph> = 5.42), Enterprising (<emph>M </emph>=<emph> </emph>34.26, <emph>SD</emph> = 5.47), and Social (<emph>M </emph>=<emph> </emph>34.03, <emph>SD</emph> = 5.65). As expected, the analysis showed a link between Conventional occupations and the Clarifier preference (see Figure ).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/3U7/01dec19/jocb241-fig-0005.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jocb241-fig-0005.jpg" title="Clarifier scores across Holland's six categories." /> </p> <p></p> <p>The second ANOVA repeated the same analysis for the Ideator scale. Artistic (<emph>M </emph>=<emph> </emph>34.56, <emph>SD</emph> = 6.05) had significantly higher scores, <emph>F</emph>(<reflink idref="bib5" id="ref65">5</reflink>, 20006) = 50.95, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0019" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .013, on the Ideator scale than Investigative (<emph>M </emph>=<emph> </emph>33.94, <emph>SD</emph> = 6.36), Enterprising (<emph>M </emph>=<emph> </emph>33.29, <emph>SD</emph> = 6.24), Social (<emph>M </emph>=<emph> </emph>33.03, <emph>SD</emph> = 6.48), Realistic (<emph>M </emph>=<emph> </emph>32.78, <emph>SD</emph> = 6.30), and Conventional (<emph>M </emph>=<emph> </emph>32.17, <emph>SD</emph> = 6.31). This finding showed clear support for the conceptual link between the Artistic style and the Ideator preference (see Figure ).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/3U7/01dec19/jocb241-fig-0006.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jocb241-fig-0006.jpg" title="Ideator scores across Holland's six categories." /> </p> <p></p> <p>The next comparison was on the Developer scale, which was expected to relate to the Investigative style. Developer scores were significantly higher, <emph>F</emph>(<reflink idref="bib5" id="ref66">5</reflink>, 20006) = 27.30, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0020" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .007, for Investigative (<emph>M </emph>=<emph> </emph>33.62, <emph>SD</emph> = 5.84) than Conventional (<emph>M </emph>=<emph> </emph>33.26, <emph>SD</emph> = 5.76), Realistic (<emph>M </emph>=<emph> </emph>32.97, <emph>SD</emph> = 6.09), Artistic (<emph>M </emph>=<emph> </emph>32.81, <emph>SD</emph> = 5.82), Social (<emph>M </emph>=<emph> </emph>32.50, <emph>SD</emph> = 6.35), and Enterprising types (<emph>M </emph>=<emph> </emph>32.38, <emph>SD</emph> = 6.04). This finding also supported the anticipated theoretical association between the Developer preference and Investigative occupations (see Figure ).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/3U7/01dec19/jocb241-fig-0007.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jocb241-fig-0007.jpg" title="Developer scores across Holland's six categories." /> </p> <p></p> <p>The final comparison focused on the Implementer scale, on which Realistic (<emph>M </emph>=<emph> </emph>31.96, <emph>SD</emph> = 5.07) and Enterprising (<emph>M </emph>=<emph> </emph>31.87, <emph>SD</emph> = 4.92) had the highest scores followed by Artistic (<emph>M </emph>=<emph> </emph>31.77, <emph>SD</emph> = 5.17) and Investigative (<emph>M </emph>=<emph> </emph>31.81, <emph>SD</emph> = 5.14), whereas Social (<emph>M </emph>=<emph> </emph>31.50, <emph>SD</emph> = 5.39) and Conventional (<emph>M </emph>=<emph> </emph>31.14, <emph>SD</emph> = 5.18) were the lowest. Pairwise comparisons indicated that Realistic and Enterprising were significantly higher, <emph>F</emph>(<reflink idref="bib5" id="ref67">5</reflink>, 20006) = 7.40, <emph>p </emph><<emph> </emph>.001, <ephtml> <math altimg="urn:x-wiley:00220175:media:jocb241:jocb241-math-0021" xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi mathvariant="normal">η</mi><mrow><mi>p</mi></mrow><mn>2</mn></msubsup></math> </ephtml>  = .002, than Conventional and Social; and the difference between Realistic and Enterprising was not significant. This finding provided partial support for the predicted link between the Enterprising category and the Implementer preference (see Figure ).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/3U7/01dec19/jocb241-fig-0008.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jocb241-fig-0008.jpg" title="Implementer scores across Holland's six categories." /> </p> <p></p> <hd id="AN0140455840-18">Discussion</hd> <p>As described earlier, the four fundamental stages of the creative process (Clarify, Ideate, Develop, and Implement) — each calls on a unique set of mental operations. While each stage is a key contributor to a creative outcome, such as producing original and transformational solutions to complex situations, people experience these stages differently and these differences can be measured in the form of distinct creative‐thinking preferences. People with a high preference for a particular stage will naturally direct more of their time and energy toward tasks, procedures, and operations associated with that stage. Since occupations differ with respect to the nature of the tasks, procedures, and operations endemic to their respective functions, the present study sought to determine the degree to which occupations might demand specific cognitive operations within the creative process. In a work environment, therefore, it stands to reason that jobs calling for a cognitive skill set associated with a particular stage of the creative process are likely to attract and retain individuals with a high preference for that mode of thinking.</p> <p>With the above goal in mind, we tested 17 hypotheses (see Table ) that differentially linked four distinct cognitive styles associated with the creative process, as measured by FourSight, to specific occupations. To review, these hypotheses were developed through a two‐step process.</p> <p>First, we identified the conceptual links between FourSight theory and a well‐established theory in the field of vocational psychology, namely Holland's six personality types (see Table ). Subsequent analysis of the FourSight preferences for the occupations in the present data set, grouped according to Holland's six categories, showed good support for these proposed conceptual links (see Figures , , , and). To further test the theoretical links between Holland's personality types and FourSight, future research could correlate Holland's measure of personality types with the FourSight scales.</p> <p>Second, documented evidence of the relationship between the six Holland personality types and the 17 occupations analyzed in this study were identified and, with reference to the Holland‐FourSight links established in step one, creative‐thinking preferences were predicted for each of the 17 occupations. Table  provides a summary of the degree to which each hypothesis was supported by the findings. Twelve of the 17 hypotheses were supported. Among these occupations seven showed single peak preferences (H1, H2, H4, H5, H6, H7, H12), four showed twin preferences with the hypothesized scale possessing the highest score (H8, H9, H13, H15), and one occupation, social services (H17), showed no difference across the FourSight preferences. Partial support was achieved when the occupation showed a combination of peak preferences, scales that were significantly different from remaining scale(s), within which the predicted preference was not the highest score. Three hypotheses were partially supported (H3, H10, H14). Finally, we determined the hypothesis not to be supported when pairwise comparisons among the FourSight scales showed that the predicted preference was not significantly higher when compared to the other scales (note: in the case of K‐12 education, we predicted no difference among scales, reflecting the Integrator profile; however, this was not the case). Two hypotheses were not supported (H11, H16).</p> <p>The accuracy of these predictions suggests a strong relationship between FourSight preferences and career choices. As such, these findings expand our understanding of creative problem‐solving preferences in vocational settings, confirming what we may sense intuitively: different jobs appear to demand different cognitive preferences, and certain jobs emphasize particular cognitive operations within the CPS process. Creativity and creative problem solving are said to be in high demand. As the [<reflink idref="bib15" id="ref68">15</reflink>] reported, "Creativity, innovation, and flexibility will not be the special province of an elite. It will be demanded of virtually everyone who is making a decent living, from graphic artists to assembly line workers, from insurance brokers to home builders" (p. 25). While such statements broadly highlight the fact that creativity is required in all occupations, the predispositions toward certain aspects of creative cognition found for the occupations in the present study point to a more nuanced understanding of the relationship between work and creativity. To simply put, while it is right to argue that all occupations require creative thinking, it is not accurate to say that all occupations uniformly require the same mental operations associated with this higher order thinking skill.</p> <p>To summarize, the fields of finance and quality attract meticulous individuals with a high preference for clarifying, while jobs in design, advertising, marketing, and consulting reflect a strong preference to imagine, envision, and generate original ideas, processes associated with the Ideate preference. Engineering and IT may suit people who have patience for the painstaking details of developing, while sales, human resources, and purchasing are more likely to engage persistent, results‐focused people with a preference for implementing. Social services, with its focus on serving the needs of all community members, seem to attract Integrators who balance all four preferences and focus on developing effective relationships with all people, no matter their preference.</p> <p>As noted earlier, three hypotheses were determined to be partially supported. These results provide deeper insight into the dynamics of FourSight theory and the complexity of thought required by particular jobs. For example, operations, which we predicted would have a Clarifier preference, showed both a high Clarifier and Implementer preference. This may underscore the fact that the trouble‐shooting activities associated with operations requires a dual focus, that is a tendency to gather information and analyze the present situation and then to use this diagnostic thinking as a springboard for action that successfully addresses a problematic situation. R&D, which we predicted would show a Developer preference showed a three‐way preference for Clarifier, Ideator, and Developer. Within corporate structures, this three‐way style makes sense. The R&D function is tasked with basic and applied research that results in the discovery of solutions to consumer problems. This investigative process is intended to lead to new products, processes and knowledge. This aligns nicely with the first three steps of the CPS process, namely identifying interesting problems (Clarify), generating imaginative possibilities (Ideate), and testing and refining the most promising ideas into workable solutions (Develop). Of less concern to this function is the implementation phase of the business process. Communications and PR, which we predicted would possess an Implementer mindset, showed both an Ideator and Implementer preference. This combination reflects a proclivity for divergent and visionary thinking, yet with an inclination toward action. The combination of FourSight preferences described above, as well as those found for other occupations (i.e., IT, engineering, HR, Purchasing), reflects a more complex picture of creative‐thinking preferences and operations associated with an occupation. This is akin to Holland's theory in which careers can be associated with single personality types or combinations thereof.</p> <p>The two hypotheses that were not supported both related to the field of education. Using Holland's theory as a guide, which associates higher education with the Investigative personality type, we anticipated an inclination toward the Developer preference. Instead, our higher education sample showed a significant tendency toward the Ideator mindset. Holland's theory suggests that individuals with a Social personality type should be overly represented in K‐12 education. Thus, we predicted K‐12 educators would show a tendency toward the Integrator creative problem‐solving style. Instead, the present results showed a propensity toward the Implementer preference. While these findings diverged from the hypotheses derived from Holland's theory, which may be a reflection of the conceptual distinctions between the two theories, the FourSight findings would seem to highlight logical conclusions. In retrospect, it makes sense that those attracted to work in higher education have a tendency toward the original thinking and independent mindedness associated with the Ideator preference. "Ivory Towers", the oft‐used term to describe university environments is indicative of this mindset. In contrast, the work responsibilities of K‐12 educators, delivering instructional lessons on a daily basis, would seem to be a good fit for those who thrive in an action‐oriented work environment.</p> <p>The connections found between FourSight preferences and occupations augur some of the standard implications derived from person–environment fit theory. Namely, the degree of fit between an individual's personality and the demands of his or her job will predict satisfaction and performance at work. Specifically, since the present study established the tendency for certain occupations to show an inclination toward some FourSight preferences over others, it might be insightful to assess the level of job satisfaction of employees based on the degree to which their FourSight profiles match the creative‐thinking preferences associated with their respective occupation. For example, extrapolating from the present study, would high Clarifiers in finance show greater job satisfaction, and perhaps less stress, than individuals with low Clarifier preferences in the same occupation?</p> <p>With respect to creative performance in the workplace, past research conducted by Puccio, Treffinger and Talbot ([<reflink idref="bib31" id="ref69">31</reflink>]) revealed that individuals' adaptor‐innovator style (Kirton, [<reflink idref="bib11" id="ref70">11</reflink>]) differentially aligned with the characteristics of creative products they produced at work. They argued that to achieve the integration of the full spectrum of qualities that comprise creative products, teams in organizations should include members with different cognitive styles. Germane to the present study, Sharif's ([<reflink idref="bib37" id="ref71">37</reflink>]) recent theoretical paper used Holland's personality types to forward a similar argument. Sharif suggested since the realization of innovative outcomes occurs mainly at a team level, and that Holland's personality types are likely to reflect different aspects of the creative process, organizations should form diverse teams based on Holland's personalities. The results of the present study, namely the apparent relationships between Holland's personality types and the creative‐process preferences measured by FourSight, provide some empirical support for Sharif's theoretical argument. The uneven distribution of creative‐process preferences within occupations and functional areas in organizations highlights the fact that the natural forces of attraction–selection–attrition (Schneider, [<reflink idref="bib34" id="ref72">34</reflink>]) in work environments may facilitate homogeneity in thought rather than the diversity necessary for innovation. While diversity has been shown to improve a team's innovation performance (West, [<reflink idref="bib39" id="ref73">39</reflink>]), forming a team around cognitive diversity may not always be practical. In such cases, it may be advantageous to provide existing team members with awareness of their creative‐process preferences and training in CPS. Awareness and training promotes the metacognitive skills to successfully navigate through the creative process, thereby increasing the probability of innovative outcomes. DeCustatis ([<reflink idref="bib5" id="ref74">5</reflink>]) conducted a comparative case analysis of teams working at IBM and reported the benefits of using FourSight theory for awareness and training. As he concluded:</p> <p>Teams exposed to the breakthrough thinking process have a higher likelihood of approaching problems deliberately. The more conversant teams are in the dynamics of breakthrough thinking, the more confident they are likely to be in compensating for preference gaps in the strengths of their team. (p. 163)</p> <p>The connection between creative‐process preferences and occupation established by the present study should serve as a catalyst for further investigations. As already described, future work might wish to explore the degree to which job satisfaction, work‐related stress, and creative performance are predicted by the interaction between individuals' FourSight preferences and the demands of their work. Furthermore, longitudinal work could be carried out that explores the extent to which individuals with particular creative‐process preferences are attracted to, and selected by, certain occupations, job functions, work environments, and degree programs. It could also be potentially valuable for such longitudinal studies to consider attrition from work environments and degree programs. Perhaps work‐related turnover or withdrawal from degree programs might be explained in part by a lack of fit.</p> <p>Numerous reports show an increased recognition that creativity is central to success in the workplace (Puccio et al., [<reflink idref="bib27" id="ref75">27</reflink>]). As the role of creativity at work expands, studies that explore the dynamics associated with creative‐process preferences may become increasingly more valuable. The findings produced by such studies could yield valuable contributions to a range of topics, including talent development, career counseling, and leadership effectiveness.</p> <p>Finally, there are aspects of the present study that can be improved in future investigations. For instance, the process used to code occupations relative to Holland's personality types could be made more rigorous through the use of inter‐judge reliability methods. Also, the present study used a limited range of occupations; it would be wise for future work to examine an expanded and more precise set of occupations. With respect to the latter point, it would be useful to take broad occupations, such as higher education, and test whether FourSight preferences vary across disciplines, departments, and functions within this profession. Lastly, future work may want to consider how the relationship between style theories and occupations may change in accordance to both micro‐factors, such as evolving job tasks, and macro‐factors, such as team climate, organizational culture, economic conditions, and socio‐cultural variables.</p> <ref id="AN0140455840-19"> <title> References </title> <blist> <bibl id="bib1" idref="ref28" type="bt">1</bibl> <bibtext> Anderson, L.W., & Krathwohl, D.R. (Eds.) (2001). A taxonomy for learning, teaching and assessing: A revision of Bloom's Taxonomy of educational objectives (Complete edn). 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  Data: Differences in Creative Problem-Solving Preferences across Occupations
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  Data: <searchLink fieldCode="AR" term="%22Puccio%2C+Gerard+J%2E%22">Puccio, Gerard J.</searchLink><br /><searchLink fieldCode="AR" term="%22Miller%2C+Blair%22">Miller, Blair</searchLink><br /><searchLink fieldCode="AR" term="%22Acar%2C+Selcuk%22">Acar, Selcuk</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Creative+Behavior%22"><i>Journal of Creative Behavior</i></searchLink>. Dec 2019 53(4):576-592.
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  Data: Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
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  Data: 17
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  Data: 2019
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  Label: Document Type
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  Data: Journal Articles<br />Reports - Research
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  Label: Descriptors
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  Data: <searchLink fieldCode="DE" term="%22Creativity%22">Creativity</searchLink><br /><searchLink fieldCode="DE" term="%22Problem+Solving%22">Problem Solving</searchLink><br /><searchLink fieldCode="DE" term="%22Preferences%22">Preferences</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Processes%22">Cognitive Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Career+Choice%22">Career Choice</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction%22">Prediction</searchLink><br /><searchLink fieldCode="DE" term="%22Finance+Occupations%22">Finance Occupations</searchLink><br /><searchLink fieldCode="DE" term="%22Creative+Thinking%22">Creative Thinking</searchLink><br /><searchLink fieldCode="DE" term="%22Occupations%22">Occupations</searchLink><br /><searchLink fieldCode="DE" term="%22Work+Attitudes%22">Work Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Work+Environment%22">Work Environment</searchLink><br /><searchLink fieldCode="DE" term="%22Stress+Variables%22">Stress Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Labor+Turnover%22">Labor Turnover</searchLink><br /><searchLink fieldCode="DE" term="%22Job+Satisfaction%22">Job Satisfaction</searchLink>
– Name: DOI
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  Data: 10.1002/jocb.241
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  Data: 0022-0175
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: FourSight theory contends that individuals show preferences for the mental operations rooted in the creative process. The four fundamental preferences measured by FourSight are Clarifiers, Ideators, Developers, and Implementers. The present study examined the extent to which certain occupations reflect a proclivity for these four creative-process preferences. Guided by Holland's theory of vocational choice, hypothesized relationships were formulated for the link between FourSight theory and 17 occupations. For example, it was predicted that those who work in finance would show a significant bias toward the Clarifier preference. Of the 17 hypothesized relationships between FourSight and occupation, statistical analysis of the FourSight preferences for 20,784 individuals showed support for 12 predictions and partial support for two of the hypothesized relationships. These findings clearly demonstrate that particular occupations engage specific creative-process preferences. Future investigations might wish to examine the degree to which the interaction between work and creative-thinking preferences predicts creative performance, satisfaction, stress, and turnover.
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        Value: 10.1002/jocb.241
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      – Text: English
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      Pagination:
        PageCount: 17
        StartPage: 576
    Subjects:
      – SubjectFull: Creativity
        Type: general
      – SubjectFull: Problem Solving
        Type: general
      – SubjectFull: Preferences
        Type: general
      – SubjectFull: Cognitive Processes
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      – SubjectFull: Career Choice
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      – SubjectFull: Prediction
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      – SubjectFull: Finance Occupations
        Type: general
      – SubjectFull: Creative Thinking
        Type: general
      – SubjectFull: Occupations
        Type: general
      – SubjectFull: Work Attitudes
        Type: general
      – SubjectFull: Work Environment
        Type: general
      – SubjectFull: Stress Variables
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      – SubjectFull: Labor Turnover
        Type: general
      – SubjectFull: Job Satisfaction
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      – TitleFull: Differences in Creative Problem-Solving Preferences across Occupations
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