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Creative performance on the job

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Title:
Creative performance on the job does openness to experience matter?
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Book
Language:
English
Creator:
Pace, Victoria L
Publisher:
University of South Florida
Place of Publication:
Tampa, Fla.
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Subjects

Subjects / Keywords:
Personality test
Personality facets
Context specificity
Five-factor model
Neo pi-r
Dissertations, Academic -- Psychology -- Masters -- USF   ( lcsh )
Genre:
government publication (state, provincial, terriorial, dependent)   ( marcgt )
bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )

Notes

Abstract:
ABSTRACT: Finding what is alike among the personalities of creative people has been a dream of many researchers. No single personality type has been discovered as prototypical, yet the promise of common attributes among creative people remains enticing. This study examines one of these promising characteristics - Openness to Experience, a personality factor from the Five-Factor Model. This factor has been shown to correlate positively with creativity in past studies. In the present study this relationship was partially confirmed in a sample of employees whose jobs require technical problem solving, by correlating the employees self-rated Work-specific Openness to Experience and NEO PI-R Openness with supervisory ratings of their creative work performance. The Work-specific Openness scale demonstrated a significant correlation with supervisory ratings of creativity, whereas the NEO PI-R Openness scale did not.
Thesis:
Thesis (M.A.)--University of South Florida, 2005.
Bibliography:
Includes bibliographical references.
System Details:
System requirements: World Wide Web browser and PDF reader.
System Details:
Mode of access: World Wide Web.
Statement of Responsibility:
by Victoria L. Pace.
General Note:
Title from PDF of title page.
General Note:
Document formatted into pages; contains 72 pages.

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University of South Florida
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Resource Identifier:
aleph - 001680951
oclc - 62392582
usfldc doi - E14-SFE0001171
usfldc handle - e14.1171
System ID:
SFS0025492:00001


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ABSTRACT: Finding what is alike among the personalities of creative people has been a dream of many researchers. No single personality type has been discovered as prototypical, yet the promise of common attributes among creative people remains enticing. This study examines one of these promising characteristics Openness to Experience, a personality factor from the Five-Factor Model. This factor has been shown to correlate positively with creativity in past studies. In the present study this relationship was partially confirmed in a sample of employees whose jobs require technical problem solving, by correlating the employees self-rated Work-specific Openness to Experience and NEO PI-R Openness with supervisory ratings of their creative work performance. The Work-specific Openness scale demonstrated a significant correlation with supervisory ratings of creativity, whereas the NEO PI-R Openness scale did not.
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Creative Performance on the Job: Does Openness to Experience Matter? by Victoria L. Pace A thesis submitted in partial fulfillment of the requirements for the degree of Master of Arts Department of Psychology College of Arts and Sciences University of South Florida Major Professor: Michael T. Brannick, Ph.D. Walter C. Borman, Ph.D. Bill N. Kinder, Ph.D. Date of Approval: April 4, 2005 Keywords: personality test, personality facets, context specificity, five-factor model, NEO PI-R Copyright 2005 Victoria L. Pace

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Dedication I would like to dedicate this manuscript to my children, Kirsten and Taylor, who have (patiently for the most part) waited for me to get “just one more thing” done before taking care of their needs and desires. They have often inspired me to set an example by aiming high, committing myself to goals, and maintaining self-discipline in the tough times as well as the easy ones.

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Acknowledgements I would like to acknowledge the help and patience of my major professor, Dr. Michael Brannick. Through many trials he stood ready to assist and allowed me to follow a path that sometimes tended to diverge from established routines, but that allowed me to achieve academic and professional goals. I would also like to acknowledge the kind support and insightful comments given to me by committee members, Dr. Walter Borman and Dr. Bill Kinder. Additionally, I would like to thank several undergraduate assistants (Jill Cantrell, Katherine Karr, Galatiani Maglis, Aida Progri, Iravonia Rawls, and Zachary Staley) who provided support in the data collection phase and listened with interest as I worked out study details and explained analyses.

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i Table of Contents List of Tables................................................................................................................. ....iii List of Figures................................................................................................................ ....iv Abstract....................................................................................................................... ........v Creative Performance on the Job: Does Openness to Experience Matter?.........................1 Aesthetics..............................................................................................................12 Fantasy..................................................................................................................13 Feelings.................................................................................................................13 Values....................................................................................................................14 Ideas......................................................................................................................14 Actions..................................................................................................................15 Hypotheses............................................................................................................16 Hypothesis 1..............................................................................................16 Hypothesis 2..............................................................................................16 Hypothesis 3...............................................................................................16 Hypothesis 4..............................................................................................16 Method......................................................................................................................... ......18 Student Study.........................................................................................................18 Participants.................................................................................................18 Procedure...................................................................................................18 Employee Study....................................................................................................20 Participants................................................................................................20 Procedure..................................................................................................21 Predictor Measures................................................................................................23 NEO PI-R Openness Scale........................................................................23 Work-specific Openness Scale.................................................................23 Criterion Measures................................................................................................24 Self-rated Creativity at Work Scale........ ................ ............. ............. ........24 Rating Form..............................................................................................24 Results........................................................................................................................ .......25 Hypothesis 1..........................................................................................................30 Hypothesis 2..........................................................................................................30 Hypothesis 3..........................................................................................................30 Hypothesis 4..........................................................................................................36

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ii Discussion..................................................................................................................... ....38 Context Specificity................................................................................................38 Differential Validity of Facets..............................................................................39 Prediction of Other Criteria..................................................................................40 Additional Comments...........................................................................................42 Directions for the Future.......................................................................................43 References..................................................................................................................... ....46 Appendices..................................................................................................................... ...50 Appendix A: Factor Pattern Matrix in Student Study...........................................50 Appendix B: Work-specific Openness Scale........................................................52 Appendix C: Sample NEO PI-R Openness Scale Items.......................................55 Appendix D: Supervisory Rating Form................................................................57 Appendix E: Boxplots for Predictor and Criterion Variables...............................59

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iii List of Tables Table 1 Statistics for Scales in the Student Study .................................................20 Table 2 Statistics for Scales in the Employee Study..............................................26 Table 3 Correlations between Facets for Openness Scales in the Student Study......................................................27 Table 4 Correlations between Facets for Openness Scales in the Employee Study..................................................28 Table 5 Validities of NEO PI-R and Work-specific Openness Total and Facet Scores in the Employee Study.........................................................29 Table 6 Correlations among Criterion Measures in the Employee Study..............30 Table 7 Hierarchical Regression of Hypothesized Blocks of Work-specific Openness Facets onto Supervisory Ratings......................34 Table 8 Hierarchical Regression of Revised Blocks of Work-specific Openness Facets onto Supervisory Ratings......................35 Table 9 Hierarchical Regression of Hypothesized Blocks of Work-specific Openness Facets onto Self-Ratings...................................35 Table 10 Hierarchical Regression of Work-specific and NEO PI-R Openness Totals onto Supervisory Ratings.............................37

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iv List of Figures Figure E1 Boxplots for Work-specific and NEO PI-R Openness Totals...................60 Figure E2 Work-specific Openness Facet Scal e Boxplots........................................61 Figure E3 NEO PI-R Openness Facet Scale Boxplots..............................................62 Figure E4 Supervisory Creativity Rating Boxplot.....................................................63 Figure E5 Self-rated Creativity Boxplot.......... ................ ................ ................ ..........63 Figure E6 Overall Performance Rating Boxplot........................................................64 Figure E7 Technical Proficiency Rating Boxplot. .....................................................64

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v Creative Performance on the Job: Does Openness to Experience Matter? Victoria L. Pace ABSTRACT Finding what is alike among the personalities of creative people has been a dream of many researchers. No single personality type has been discovered as prototypical, yet the promise of common attributes among creati ve people remains enticing. This study examines one of these promising characteristics—Openness to Experience, a personality factor from the Five-Factor Model. This factor has been shown to correlate positively with creativity in past studies. In the present study this relationship was partially confirmed in a sample of employees whose jobs require technical problem solving, by correlating the employees’ self-rated Work-specific Openness to Experience and NEO PI-R Openness with supervisory ratings of their creative work performance. The Workspecific Openness scale demonstrated a significant correlation with supervisory ratings of creativity, whereas the NEO PI-R Openness scale did not. Although none of the NEO PIR facets were significant predictors of the criterion, four Work-specific facets were significant predictors based on zero orde r correlations. These facets are Openness to Ideas, Fantasy, Values, and Actions. However, although individual facets of Openness were expected to differ in validity, the magnitude of their correlations with creative performance scores did not differ significan tly. Convincing results showing incremental validity of the Work-specific scale over the NEO PI-R scale are also discussed.

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1 Creative Performance on the Job: Does Openness to Experience Matter? “In my view, creativity is best described as the human capacity regularly to solve problems or to fashion products in a domain, in a way that is initially novel but ultimately acceptable in a culture.”-Howard Gardner (1989, p. 14) Creativity—we all admire it, wish we had it or had more of it and use it as a description of people, products, problem soluti ons and ideas. But what is it and how does it come to be? We may define creativity in terms of the process by which one creates, the individual characteristics necessary for a person to be creative, the environments that encourage creativity, or the qualities of the product produced. Simonton (1988) outlined the “four p’s” of creativity: Process—the cognitive approach Product—the resultant idea or object that is original and useful Person—characteristics of the individual who engages in the process to create the product Persuasion—the necessary social co nstruct involved in recognition and implementation of a creative product Although Simonton’s favorite “p” appears to be persuasion, I prefer to focus on the creative person because the role of the idea champion, or persuader, is not necessarily filled by the product creator. Indeed, independent sets of personality characteristics, which may or may not reside in the same indi vidual, may be involved in these two roles.

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2 Torrance (1988) chose to focus on process. In his words, the process involves “sensing difficulties, problems, gaps in info rmation, missing elements, something askew; making guesses and formulating hypotheses about these deficiencies; evaluating and testing these guesses and hypotheses; possibly revising and retesting them; and finally communicating the results” (p. 47). Understanding the creative process could prove fruitful in the development of training programs to increase creativity. Whether a specific process leads reliably to creativity would be an important question for determining training effectiveness. Of course, Torrance pointed out that there might be a particular kind of person that is likely to use this process successfully. Alternatively, Amabile (1996, p. 35) offered a product-based definition of creativity: “A product or response will be judged as creative to the extent that (a) it is both a novel and appropriate, useful, correct or valuable response to the task at hand, and (b) the task is heuristic rather than algorithmi c.” The second part of this definition refers to process. Amabile described heuristic tasks as those that lack well-defined steps that can be followed to reliably produce a solution. The main focus of the definition remains on product. In the final analysis, the bottom line for determining individual creative success at work is the quality and quantity of an individual’s creative products, so the appropriate place to consider product seems to be on the criterion side. If we are attempting to predict creativity, effective processes and environments for achieving creativity should result in consistently creative products. Highly creative individuals should also generate creative products.

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3 Historically, personal characteristics have been the most popular focus of creativity research. Feist made the case for the influence of personality on creative achievement by pointing to evidence of “two criteria of causality: covariance and temporal precedence” (1999, p. 274). Many researchers have been interested in pinpointing stable personality traits that covary with creative ability. Although past research has had mixed success in identifying these traits, narrowing the domain in which individual creativity is expressed and looking at achievement rather than ability as the criterion may allow a more accurate assessment of the influence of personality on creativity. In regard to the temporal precedence requirement for causation, basic personality is determined very early and may be partially genetically based; therefore, it seems likely that personality precedes creative achievement. Because identification of creative personality types could later prove important for recruitment and selection, this is an inte resting research avenue Before attempting to learn more about creative persons, we should stop to consider the possible benefits of identifying them. Feist eloquently expre ssed the importance of such an endeavor: “Universities, businesses, the arts, entertainment, and politics—in other words, all of the major institutions of modern society—are each driven by their ability to create and solve problems originally and adaptively, that is, creatively. Therefore, the ultimate success and survival of these institutions depend on their ability to attract, select, and maintain creative individuals” (1999, p. 289). Since Guilford’s Presidential Address to the American Psychological Association in 1950, researchers have been looking for personality factors common among creative persons, task and environmental factors that encourage or inhibit individual creativity,

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4 and interventions such as training or education that affect the development of creativity. Particularly in early research, individual factors received the most research attention. In studies at the Institute of Personality Assessment and Research (IPAR) at the University of California at Berkeley from 1950 to 1970, begun under D.W. MacKinnon, the focus was to find individual determinants of “effective functioning” (Barron, 1988, p. 81). Participants in these studies were creative individuals from the fields of writing, architecture, mathematics, physical sciences and engineering research who were nominated by experts within their fields. Over the course of a weekend, several psychologists assessed the individual characteristics of these participants. Later, their ratings were compared to ratings of “less creative professionals in a field who were matched for age and geographic locations of their practice and assessed through a battery of procedures sent to them through the mail” (Sternberg & O’Hara, 1999, p.260). Although creativity is correlated with intellig ence over the full rang e of cognitive ability, Barron found that, “beyond an IQ level of about 120, however, measured intelligence is a negligible factor in creativity” (1963, p.242 as cited in Sternberg & O’Hara, 1999, p. 261). Among individuals who are qualified for a particular job, it is very unlikely that a full range of cognitive ability will be represen ted. Therefore, it may be especially useful to assess personality and other predictors of creativity in this context. Of course, because people do not create in a vacuum, creative performance is not entirely a function of individual attributes. Instead, interactions between person variables, task characteristics, and environmental variables are likely to exist. However, perhaps partly due to intuitive appeal, personality correlates of creativity have been a focus. Is there a certain mix of personality factors that makes one inherently creative, or is

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5 creativity more dependent on external fact ors? Because some pers onality factors have been shown to exhibit high levels of stability, a demonstrated relationship between personality factors and creative performance mi ght help us predict which job applicants are likely to be most productive and innovative in creative fields or which children should consider training in artistic and investigativ e areas. If individuals with the most promising characteristics can be selected, their promise can then be realized and optimized through the application of theories about environmental structuring and management. This study will focus on personal variables as indicators of potential creative production. One expectation is that creative performance may be relatively stable over time, but not across situations. Within a particular type of job, a person’s creative production level may differ under various work conditions, but it is lik ely to differ much less than the creative production levels of different individuals under the same work conditions. As Feist concluded, “The traits that distinguish creative children and adolescents tend to be the ones that distinguish creative adults. The crea tive personality tends to be rather stable.” (1999, p. 290) Although it is possible that creative potential may be stable across situations, creative performance as operationalized by ratings of demonstrated creativity may be more domain-specific. Because I am interest ed in the correlation between personality factors and demonstrated creative productivity at work, both variables were measured specifically in th e work context. If the creative personality is relatively stable, then why have psychologists had such difficulty in determining reliable characteristics of a prototypical creative personality? Unfortunately, research about the creative pers onality has shown

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6 inconsistent relationships between hypothesized predictors and rated creativity (MacKinnon, 1978). Attempts to measure creati vity have often used tests of divergent thinking, such as those created by Guilford or Torrance. Barron & Harrington (1981) noted that divergent thinking scores often failed to correlate with measures of creative achievement and proposed that one reason for this failure may be the field specificity of divergent thinking abilities. Although cert ain personality fact ors seem generally connected with creativity, Helson conclude d, “we cannot expect the personalities of people who create in different domains to be the same, or to differ in the same ways from comparison subjects” (1996, p. 303). Accordingly, it is reasonable to hypothesize that the importance of specific personality factors varies across work domains. Another aspect of creative individuals that makes them difficult to characterize consistently is that they may select particular, sometimes narrow, domains in which to focus their creative abilities. In unselected domains, they may virtually ignore creative opportunities. Because of this selectivity, meas ures that assess creativity correlates across multiple domains may be doomed to failure by a person’s elevated levels in one domain being counterbalanced by low or average levels in another domain. Tardif and Sternberg (1988, p. 434) found this “Creative in a particular domain” characteristic of creative persons is written about by more cited authors than any other listed cognitive characteristic, except “Uses existing knowledge as base for new ideas.” Although there are many hypothesized reasons for individual creativity being concentrated in certain domains, there is widespread recognition th at an individual may display creativity in some domains more than others. Of course there are authors who have argued against domain specificity (Plucker, 1998). As Hocevar stated, however, “intuitively it is

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7 plausible that a person who is creative in one area has neither the time, ability, nor the motivation to be creative in other areas” (1981, p. 457). Although not entirely a settled matter, the prevailing view is that creativity, at least as assessed through the quality of creative achievement, is likely to be some what domain specific (Baer, 1998; Runco, 1987). Baer conducted several studies in which rated creativity of products in different domains produced by the same individual showed low correlations (an average of .06 in one study). The Runco study found the average correlation between creative quality scores from different domains to be .16. Because these studies involved children and adolescents as participants and did not adequately assess correlations within domains, more research is needed in this area. Nevertheless, creative performance assessments in the same domain have shown “fairly robust lo ng-term stability” as illustrated by Baer’s study of creativity in story writing measured in 9-year-olds and again when they were 10 (as cited in Baer, 1998, p. 174). Due to hypothesized domain specificit y, this study focused on individuals working in jobs that require problem solving of a technica l nature. It examined the validity of personal characteristics for predicting creative production in this area. What kinds of individual characteristics help us to predict an individual’s level of creative production? Do these characteristics vary across domains? Piirto (1992) named three domains of creativity: problem solving, artistic, and social/leadership. For a creative idea to have appeal for others and to be recognized sufficiently to lead to further development, ability in all three domains must be used. Nevertheless, it is the problem-solving domain that is the focus this study.

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8 Certainly, to solve problems creatively, it is necessary to be aware of the problem’s existence (Farr & Ford, 1990). Awareness of discrepancies and unique aspects in one’s environment might inspire a desire for change (Simonton, 1988). Barron (1988, p. 95) described the creative person as po ssessing “alertness to opportunity,” “keen attention,” and “a drive to find pattern and meaning.” He also listed the following qualities: “Openness to new wa ys of seeing,” “intuition,” “a liking for complexity as a challenge to find simplicity,” “independence of judgment that questions assumptions,” “willingness to take risks” and “unconventionality of thought that allows odd connections to be made.” In creative fields, Csikszentmihalyi asserted that, “A person who is attracted to the solution of abstract problems (theoretical value) and to order and beauty (aesthetic value) is more likely to persevere.” (1999, p. 332). These qualities seem quite compatible with the personality construct Openness to Experience from the Five-Factor model (McCrae, 1993-94). Indeed, empirical studies have found a correlation between creativity and Openness to Experience (Feist, 1999; George & Zhou, 2001; King, Walker & Broyles, 1996; MacKinnon, 1978). McCrae provided three possible reasons for this relationship: (1) “open people may be more fascinated with the open-ended, creative, problem-solving tasks and they may simply score higher on such tasks,” (2) they “may have developed cognitive skills associated with creative, divergent thinking, namely flexibility and fluidity of th ought,” and (3) they “may ha ve an interest in seeking sensation and more varied experiences, and this experiential base may serve as the foundation for flexibility and fluency of thinking” (1987, as cited in Feist, 1999, p. 289). In the area of technical problem solving, it is necessary to have sufficient breadth of experience as well as depth of knowledge. It stands to reason that being high in

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9 Openness to Experience leads to this breadth when an individual’s environment allows expression of this aspect of personality. Multiple experiences in one’s own field and closely related fields create depth of knowledge. Experience in weakly related fields or in seemingly unrelated fields in which parallel problems and solutions exist may provide the foundation for divergent thought about task solutions. Open individuals are more likely to seek this sort of experience. By being able to see parallels in unexpected places and translate those into one’s own field, innovative solutions can be found. By attending to not only what already exists, but what could potentially exist, new products and solutions can be generated. Therefore, this study hypothesized that individuals who are open to a wide variety of experiences would produce more creative solutions than those who prefer the familiar in life and at work. Furthermore, selecting study participants based on job type can help reveal underlying patterns of correlations between creativity at work and the six facets of Openness to Experience: Openness to Fantasy, to Aesthetics, to Feelings, to Actions, to Ideas, and to Values. Specifically, Openness to Fantasy, to Aesthetics, to Actions, and to Ideas was hypothesized to correlate more highly with creativity measures for technical personnel than would Openness to Feelings or to Values. Reasons for this hypothesis are explained later, in the sections describing each facet. People may be more or less open to expe rience depending on the area of their life that is involved. Thus, items worded specifically for the workplace may provide higher validity. For example, a person may be very creative at solving problems at work and not very open to new activities in general, such as trying new foods or attending dance concerts. Considering openness in the work context, perhaps the same person enjoys

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10 traveling to new places for conferences and thinking about the aesthetics of work products. By using job-relevant items, it may be possible to increase the correlation of this Openness scale with ratings of creative performance. There is good reason to hope that work-specific items will increase the crit erion-related validity of the Openness scale. Schmit, Ryan, Stierwalt and Powell (1995) found that school-specific versions of NEO PI-R items for the Conscientiousness scale demonstrated greater validity for predicting cumulative GPA among college students compared to standard noncontextual items. The researchers minimally reworded NEO PI-R Conscientiousness items to be more schoolspecific. One group of participants was instructed to complete the inventory as though they were applying for college admission, but with the understanding that they would actually be given a monetary incentive for meeting admission qualification standards. For these participants, the use of school-specific items increased criterion-related validity significantly over the use of more gene ral items from the original NEO PI-R ( z = 3.30, p <.05). For participants who were given only the standard instructions from the NEO PIR, the validity of school-specific items was al so higher than that of noncontextual items, but not significantly ( z = 1.25, ns .). Thus, measuring Conscientiousness as it applies to the academic setting increased the criterion-rela ted validity of that scale for predicting academic performance. If the same pattern holds for Openness, work creativity shou ld correlate more strongly with work-specific Openness whereas general creativity should correlate more strongly with general Openness as assessed by the NEO PI-R scale. In other words, an individual’s demonstrated creativity rating in the work domain may correlate more highly

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11 with their level of Openness in the same domain than with their level of global Openness as assessed by the NEO PI-R Openness Scale. Following Barron and Harrington’s advice with regard to specificity in use of biographical inventories that “the maximum scientific value of such inventories will come from examining and reflecting upon the content of item-level correlates of creative achievement in particular settings and samples” (1981, p. 465), it seems appropriate to consider both the work setting and the facet le vel of Openness to Experience. It may be useful to examine how each facet correlates with creative achievement for certain categories of employees. Paunonen and Ashton (2001) showed incremental validity for predicting criteria when five lower-level facet scores, selected by experts, were added to the regression equation that included broader factor scores. Specifically, a 9.5% mean increase in variance accounted for was observed by adding the facet scores to the equation. Although Hocevar (1981, p. 457) suggested, “different instruments should probably be used for different areas,” an appealing possibility is that of using a common measure of work-specific items that tap pers onality constructs from the Five Factor Model and differentially weighting facet scores for prediction of performance in different job areas. This study explores relationships between facets of Openness and creative achievement of personnel in problem solving occupations. Openness to experience as conceptualized by Costa & McCrae (1992) consists of six facets described below: Openness to Aesthetics, Openness to Fantasy, Openness to Feelings, Openness to Values, Openness to Ideas, and Openness to Actions.

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12 Aesthetics Openness to Aesthetics implies sensitivity to and appreciation of beauty, order and artistic interests. Although our application of this term is often limited to artistic endeavors, aesthetic sensibility is applicable to a wide range of fields. Preferences for symmetry and complexity have been observed in highly creative individuals (MacKinnon, 1978). But as Barron stated (1988, p. 93), “To prefer a complex phenomenal display is not in itself a mark of creativity, unless it is coupled with an unrelenting drive to find a simple order. Simplicity in complexi ty, unity in variety— these are the criteria for beauty and elegance, in art, mathematics, science, and personal consciousness in general.” As Tardif and Sternberg (1988) pointed out, a common strength among creative people is their recogni tion of worthwhile problems on which to work. This requires awareness of the aesthetic qualities of these problems. This ability is most critical in the research phase. Once a suitable task has been chosen, aesthetic sensibilities continue to play a role in solu tion development. In what way can the needs of internal or external consumers be addressed efficiently, effectively, and elegantly? It is the combination of these three qualities with novelty that helps define an aesthetically pleasing creative solution. And because aesthetic quality is also based partly on shared preferences and sensual appeal to knowledgeable consumers, individuals who score higher on Openness to Aesthetics might be expected to produce more attractive product and service ideas that, if implemented, will be more successful with consumers both inside and outside the employing organization. In turn, these factors should increase creative performance ratings for these individuals. For this reason, the Aesthetics facet

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13 was expected to correlate moderately with supervisory ratings for the employees in this study. Fantasy Openness to Fantasy concerns the propensity of an individual to daydream and to create imaginative and often elaborate scenarios of what could be, rather than to focus on pragmatic concerns and the current state of affairs. Feist (1999) cited numerous studies linking fantasy-orientation and imagination to creativity. Frese expressed the importance of allowing employees to spend time “dreaming up new products or ideas” for innovation over the long run, even though such time use might encounter resistance in companies seeking to increase short term effectiveness (2000, p. 430). For jobs that require problem solving, a moderate correlation between Openness to Fantasy and supervisory ratings of creativity was expected. Feelings Openness to Feelings addresses the level of an individual’s awareness of their own affective states. Those who are aware of their own emotions also tend to value these emotions. They may also be more aware of external cues to others’ feelings, causing them to respond more appropriately to the emotional states of others. In the IPAR studies mentioned earlier, creative subjects indicated a greater openness to feelings and emotions than would be expected (MacKinnon, 1978). However, these studies were based on inform ation about creative subjects from a variety of professional fields, so this observation could mask significant differences in openness to feelings across jobs. For example, later st udies that sought to differentiate personality characteristics of creative persons in scientific and artistic fields found creative scientists

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14 to be less open to feelings as a group than were creative artists (Feist, 1999). Perhaps this is due to the difference in emphasis placed on feelings in the two fields. Whereas artistic training often encompasses exercises aimed at gaining awareness of one’s own affective reactions, the role of affect is seldom considered or discussed in scientific training. This may cause individuals with very high openness to feelings to seek out fields where recognition of feelings is more central to jo b tasks. Because those involved in technical problem solving occupations are likely to be mo re similar to scientists than artists, some range restriction on this facet in the employee sample was expected. Based on this expectation, a low correlation between Openness to Feelings scores and creative productivity ratings was predicted for this group of employees. Values The Openness to Values facet is a measure of an individual’s inclination to tolerate diverse lifestyles and priority systems. Rather than believing there is one true or right way to live, people high on openness to values tend to adopt an individualistic concept of right and wrong. There are few hard and fast rules that all should follow for such people. Toward the opposite end of the continuum, people who are lower on openness to values tend to conform to convention and to view right and wrong as universal and stable truths. Little or no re lation between Openness to Values and rated work creativity was expected to exist for this sample of employees. Ideas Openness to Ideas implies intellectual cu riosity and an interest in abstract philosophical topics. Exploration of a variety of complex and sometimes conflicting ideas is a welcome challenge for those who are high on this facet. Puzzles, word games

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15 and related pastimes are generally enjoyable to these individuals. Sternberg & Lubart’s Investment Theory of Creativity posited that creative individuals aptly pursue “ideas that are unknown or out of favor but have growth potential” (1999, p. 10) and persist in persuading others of their value. According to MacKinnon (1978) and Hocevar (1981), theoretical values, as measured on the Allport-Vernon-Lindzey (1951) Study of Values, were shown to be highly important to crea tive persons. Walberg told us, “Creativity (including problem finding and solving) is the trial-and-error search for novel and useful solutions by combinations of stored and externally found elements.” (1988, p. 346). Clearly, awareness of and interest in new ideas is critical to the creative endeavor. The Openness to Ideas facet was expected to yield the greatest predictive power for creativity in this sample. Actions The final facet, Openness to Actions, indicates willingness to do new things and to explore actively. People who are open to actions prefer new experiences to established routines. They are comfortable with change and may be considered adventurous. A willingness to act in different ways may l ead to encounters with new things and new people. These encounters may yield fresh insights that are important to the creative effort. Therefore, it was expected that this facet would be a moderately important predictor of work creativity for this sample. In the past, most studies of the correlates of openness focused on the global Openness construct. A thorough search of the literature revealed no study that attempted to look at the importance of specific Openness facets in relation to creative production. Facets may differ in their relevance to creativity, so Openness to Experience was

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16 measured at the facet level. Furthermore, Openness to Experience as measured by the NEO PI-R addresses many aspects of a pe rson’s life—from the food they eat to the religious values they hold. To measure only work-related Openness to Experience it is necessary to narrow the focus of the scale items. This was done with the new measure. Finally, additional empirical studies were needed to examine the relationships of specific Openness facets to creative production by work domain. This study adds to the body of empirical studies and differs from previous studies in the following ways: (1) measurement of Openness to Experience by facet ; (2) measurement of work-specific Openness to Experience; and (3) correlation of Openness to Experience facets with creative production for a specific job domain (technical problem solving). Hypotheses In the present study, the following hypotheses were tested: Hypothesis 1 Openness to Experience as assessed by the NEO PI-R scale will be positively correlated to creativity at work as rated by supervisors. Hypothesis 2. Scores from the Work-specific Openness scale will be positively correlated with scores from the NEO PI-R scale of Openness to Experience. Examination of this relationship is a test of convergent validity. Hypothesis 3. Facets of Openness from each of the Openness scales will differ in their ability to predict creativity in this jo b domain in the following manner: Openness to Ideas, to Fantasy, to Actions, and to Aesthetics are expected to be better predictors of creativity at work for technical personnel than are Openness to Feelings or to Values. Hypothesis 4. Life area in which creativity is measured will influence the correlation with Openness. The correlation will be higher when creativity and Openness

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17 scores are compared for the same life area and will be lower when compared across life areas. For this study, Work-specific Openness to Experience is expected to predict creativity at work better than does the NEO PI-R measure of general Openness to Experience.

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18 Method Student Study Participants. Two hundred twenty-three (223) employed undergraduate psychology students participated in the development phase of the Work-specific Openness scale. One case was not used due to obvious response problems. Eighty-eight percent (88%) of the sample was female. Average participant age was 21.3 years, with a range of 18 to 53 years. Fifty-two percent (52%) described themselves as White, 21% as Black, 16% as Hispanic, 5% as Asian, and 6% as Other. No requirement of type of job was made, and a wide variety of jobs was represented. The average number of hours worked per week ranged from 5 to 45 with a mean of 22.8. Procedure. Approximately 115 preliminary items for the Work-specific Openness and self-rated creativity scales were administered to the student sample. The Workspecific Openness items were written to me asure individual characteristics similar to those covered by the NEO PI-R Openness facets, but with more relevance to the work context. These items were interspersed with the NEO PI-R Openness and Conscientiousness scales as well as the BIDR Impression Management scale. Groups of approximately 25 students attended one of several sessions and independently completed the test items in the presence of the researcher. Responses were analyzed to determine psychometric properties of the new items. A factor analysis was computed on the Openness items to check for emergence of the six anticipated facets (see Appendix A for

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19 factor pattern results for the Work-specific items). Neither the Work-specific items nor the NEO PI-R items produced six factors corresponding to the six facets. A decision was made to select Work-specific Openness items that would maximize facet scale reliabilities while maintaining the best parallel in content with the NEO PI-R facet scales. Work-specific Openness items were also examined for item variance and difficulty level. Based on results as well as rational considerations, 48 items were selected for inclusion in the final Work-specific Openness scale. This number includes eight items for each of the six facets incorporated in the NEO PI-R Openness scale. Internal consistency statistics (coefficient alpha) for each facet as well as for the overall scale were determined to be acceptable (see Table 1) before the scale was administered to the employee group. Because this test is for rese arch rather than selection, the final test was required to meet the modest reliability level suggested for research purposes by Nunnally and Bernstein (1994) of .70. Nunnally and Bernstein (1994) suggested a minimum alpha level of .90 for tests being used for important decisions such as selection. Results from pilot testing showed mostly similar reliability le vels for the 8-item Work-specific facets and for corresponding NEO PI-R facets of Openness (Table 1). Reliability of each 48-item full scale exceeded .70. Correlation of creativity self-ratings with total scores on Open ness to Experience were computed following the pilot study as an initial check of the assumption that a correlation between creativity and openness exists. Favorable results ( r = .41, p < .01 for the NEO and r = .65, p <.01 for the Work-specific scale) led to continuation of the study with a sample of employees and employed st udents who hold jobs requiring technical problem solving.

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20 Table 1 Statistics for Scales in the Student Study MeanStandard Deviation Coefficient Alpha Work-specific Openness (total) 167.1216.10 .87 NEO Openness (total) 164.2215.90 .84 Work Values (average) 3.23.55 .68 NEO Values (average) 3.55.54 .66 Work Fantasy (average) 3.40.56 .72 NEO Fantasy (average) 3.53.50 .57 Work Aesthetics (average) 3.63.53 .74 NEO Aesthetics (average) 3.68.64 .74 Work Feelings (average) 3.80.47 .70 NEO Feelings (average) 3.97.52 .67 Work Actions (average) 3.11.58 .74 NEO Actions (average) 3.07.47 .47 Work Ideas (average) 3.60.49 .70 NEO Ideas (average) 3.56.55 .69 Self-rated Creativity (average) 3.55.65 .84 Employee Study Participants. Research study packets were directly distributed to 246 employees from a variety of workplaces. An additional 64 packets were distributed to supervisors in two departments, who were asked to pass these on to employees. It is unknown how

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21 many of these supervisors actually did so, as no supervisor contact information was recorded and the response rates from these departments were unusually low (5% and 16%). With the additional 8 packets known to have been distributed in these departments, the total number of packets accounted for reaches 254. Most of these 254 packets were distributed to employed undergraduate students in engineering, computer information systems, and architecture at the University of South Florida, but some were distributed to U.S.F. employees in technical positions and to employees at a variety of other organizations, including an engineering firm and a government crime lab. Five was the maximum number of responses received from any particular department or business. All participants were volunteers who stated that their job required them to solve technical problems. Surveys and/or rating forms were returned from 101 packets, representing a response rate of 40%. For some of these, only the survey or the rating form was returned. One survey was returned with too many missing responses. (Only surveys with a maximum of one missing response from any Openness facet were used.) Two extreme outliers (more than three standard deviations from the mean of either of the Openness totals or supervisory ratings of creativity) were deleted. In total, 83 participants and their supervisors returned data that could be matched and used. Employee ages ranged from 19 to 57, with a mean of 31.16 and standard deviation of 10.66. The mean number of hours worked per week was 34.35 with a standard deviation of 11.05. Employee tenure at their current organizations ranged from two months to 25 years, with a mean of 4.25 years. Procedure. Study packets were distributed to voluntary participants who completed the enclosed materials and returned them by mail. Each packet included

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22 instructions and informed consent documents as well as a survey for the employee to complete and a rating form to be given to their supervisor. Self-addressed stamped return envelopes were also included. The employee survey included all questions from the NEO PI-R Openness Scale and the new 48-item Work-specific Openness Scale, interspersed with the NEO PI-R Conscientiousness Scale. Toward the end of the form was a 7-item self-rated creativity scale. Standard demograp hic items were included at the end of the survey. The completed survey did not contain the participant’s name. A list of Workspecific Openness items and a sample of NEO PI-R Openness items from the employee survey are included in Appendices B and C. Supervisory ratings of each employee’s demonstrated creativity were collected using a rating form. This form was included in the study packet given to employees. The employee was asked to give the rating form, accompanying instructions, informed consent document, and a return envelope to their supervisor. The supervisor anonymously rated the employee on five declarative statements regarding the rated employee’s quantity, quality an d dependability of creative wo rk. Two additional rating items were included on this form: an overall work performance item and a technical proficiency item. Response options for each statement follow a 5-point Likert format from Strongly Disagree to Strongly Agree. Each rating form was returned directly to the researcher, who matched it with the completed employee survey bearing the same number. No data were kept that links numbers with individual names, in order to protect the identities of employees and supervisors. A copy of the rating form is included in Appendix D.

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23 Predictor Measures NEO PI-R Openness Scale. Due to time constraints, only the Openness and Conscientiousness scales, rather than the entire NEO PI-R, were administered. Conscientiousness items were used as fillers, and also for additional research questions not included in this study. The primary purpose of using the NEO PI-R scale was to examine the convergent (construct) validity of the new Work-specific Openness Scale. The NEO PI-R Openness Scale contains 48 items and assesses six facets of Openness to Experience. Sample items are included in Appendix C. Costa and McCrae (1992, p. 44) provided coefficient alpha levels for each face t in the self-administered version for their employment sample: Fantasy (.76), Aesthetics (.76), Feelings (.66), Actions (.58), Ideas (.80), and Values (.67). Although Costa and McCrae did not provide the alpha level for the 48-item Openness scale in the test manual, they did state that NEO PI-R domain scales had alphas ranging from .86 to .95. Coefficient alpha levels found in the employee sample were mostly similar to or higher than those reported by Costa and McCrae, and are included in Table 2. Work-specific Openness Scale. The final 48 items are included in Appendix B. These 48 items were selected from a much larger pool of items, based on results of administration to a development sample. Part icipants in the development sample were employed undergraduate psychology students from USF, as described previously in the Student Study section. The Work-specific Openness items are intended to be similar in content to the NEO PI-R items, but are more relevant to the work context. The test includes both positively and negatively worded items in order to attempt to control for response sets.

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24 Criterion Measures Self-rated Creativity at Work Scale. As part of the Work-specific Openness survey, participants in the student sample completed ten Likert-scaled items concerning their own creativity at work. In the employee sample, seven Likert-scaled items were used. Scores on this measure were obtained by totaling the responses and obtaining an average item score for each person. Rating Form. A five-item Likert-style measure of supervisory ratings of the employee’s level of creativity on the job is included in Appendix D. Two additional single-item ratings were included to measure overall job performance and technical proficiency. Supervisors were expected to incorporate their judgments of employees’ products and ideas into their ratings. Though some might prefer creative production assessments to be more objective, Amabile argued, “creativity assessments must, ultimately, be socially, culturally, and histor ically bound. It is impossible to assess the novelty of a product without some knowledge of what else exists in a domain at a particular time. It is impossible to a ssess appropriateness without some knowledge of utility or meaning in a particular context” (1996, p.38). Indeed Csikszentmihalyi (1999) explicitly stated in his social systems approach that the judgment of others is what defines a creative product. And as Hocevar (1981) pointed out, supervisors view employees’ work in comparison with others and are e xperienced judges of quality. In addition, supervisory ratings are often used by businesses as the indicator of whether employees are successful in their position. Supervisors’ perceptions are the basis for many important administrative decisions affecting the employee. Therefore supervisory ratings may be the most relevant available indicator of employee creative success on the job.

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25 Results Means and standard deviations for each variable are listed in Table 1 for the student study and in Table 2 for the employee study. No serious range restriction in any of the predictor variables was noted in either study. (See Appendix E, Figures E1-E3 for boxplots of predictor variables in the employee study.) However, most criterion variables were negatively skewed as shown in Appendix E, Figures E4-E7. Overall performance and technical proficiency ratings exhibit particularly strong ceiling effects, so analyses using these two criteria should be interpreted with caution. Correlations among all Openness facet scales used in the student pilot study appear in Table 3. Similar correlations for the employee study appear in Table 4. Predictive validities of the NEO PI-R and Work-specific Openness Scales, as well as their facet subscales, are shown in Table 5. Finally, correlations between criterion scales are shown in Table 6.

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26 Table 2 Statistics for Scales in the Employee Study Mean Standard Deviation Coefficient Alpha Work-specific Openness (total) 168.82 16.03 .86 NEO Openness (total) 165.90 18.51 .88 Work Values (average) 3.39 .44 .48 NEO Values (average) 3.65 .62 .79 Work Fantasy (average) 3.39 .59 .77 NEO Fantasy (average) 3.36 .60 .75 Work Aesthetics (average) 3.64 .60 .81 NEO Aesthetics (average) 3.26 .64 .75 Work Feelings (average) 3.68 .52 .74 NEO Feelings (average) 3.66 .67 .83 Work Actions (average) 3.22 .58 .79 NEO Actions (average) 3.06 .53 .65 Work Ideas (average) 3.78 .48 .72 NEO Ideas (average) 3.75 .62 .79 Self-rated Creativity (a verage) 3.72 .66 .89 Supervisor-rated Creativity (average) 3.89 .87 .92

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27 Table 3. Correlations between Facets for Openness Scales in the Student Study (Convergent correlations in bold) Work Values Work Fantasy Work Aesthetics Work Feelings Work Actions Work Ideas NEO Values NEO Fantasy NEO Aesthetics NEO Feelings NEO Actions NEO Ideas Work Values 1 Work Fantasy .010 1 Work Aesthetics .008 .597** 1 Work Feelings .043 .317** .531** 1 Work Actions .431** .306** .197* .109 1 Work Ideas .084 .575** .574** .359** .438** 1 NEO Values .376** .215* .180* .209* .208* .319** 1 NEO Fantasy .203* .409** .326** .269** .101 .226** .307** 1 NEO Aesthetics .142 .402** .335** .276** .213* .257** .158 .332** 1 NEO Feelings .135 .348** .444** .607** .129 .194* .302** .418** .581** 1 NEO Actions .365** .217* .113 .016 .627** .237** .172* .073 .224* .067 1 NEO Ideas .092 .422** .315** .348** .347** .451** .282** .261** .506** .422** .227** 1 p<.05, **p<.01

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28 Table 4. Correlations between Facets for Openness Scales in the Employee Study (Convergent correlations in bold) Work Values Work Fantasy Work Aesthetics Work Feelings Work Actions Work Ideas NEO Values NEO Fantasy NEO Aesthetics NEO Feelings NEO Actions NEO Ideas Work Values 1 Work Fantasy .06 1 Work Aesthetics .03 .44** 1 Work Feelings -.04 .29** .23* 1 Work Actions .24* .36** .16 -.01 1 Work Ideas .17 .71** .56** .20 .46** 1 NEO Values .39** .26* .20 .18 .18 .29** 1 NEO Fantasy .21 .53** .15 .17 .29** .30** .34** 1 NEO Aesthetics -.05 .36** .50** .23* .10 .18 .14 .38** 1 NEO Feelings -.10 .28** .35** .62** -.06 .07 .10 .31** .49** 1 NEO Actions .34** .28** .28* -.03 .63** .39** .23* .23* .31** -.02 1 NEO Ideas .14 .57** .39** .27* .44** .69** .35** .40** .32** .13 .36** 1 *p<.05, **p<.01

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29 Table 5 Validities of Openness Total and Facet Scores in the Employee Study Supervisory ratings of employee creativity Self-ratings of creativity at work Supervisory ratings of overall job performance Supervisory ratings of technical proficiency Work-specific Openness .32** .73** .17 -.06 NEO PI-R Openness .09 .46** -.01 -.12 Work-specific Values .25* -.03 -.03 .17 NEO PI-R Values .10 .11 -.16 -.002 Work-specific Fantasy .26* .69** .18 -.10 NEO PI-R Fantasy .11 .30** .08 -.11 Work-specific Aesthetics .08 .56** .11 -.07 NEO PI-R Aesthetics -.05 .29** -.11 -.18 Work-specific Feelings .15 .26* .05 -.04 NEO PI-R Feelings -.11 .14 -.02 -.15 Work-specific Actions .22* .43** .10 -.15 NEO PI-R Actions .12 .28* .04 -.07 Work-specific Ideas .25* .73** .22 .01 NEO PI-R Ideas .21 .62** .15 .06

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30 Table 6 Correlations among Criterion Measures in the Employee Study Supervisory ratings of employee creativity Self-ratings of creativity at work Supervisory ratings of overall job performance Supervisory ratings of employee creativity 1 Self-ratings of creativity at work .22 1 Supervisory ratings of overall job performance .60** .20 1 Supervisory ratings of technical proficiency .21 -.16 .44** Most of the hypotheses were supported or partially supported as follows: Hypothesis 1 Openness to Experience as assessed by the NEO PI-R scale is positively correlated to creativity at work as rated by supervisors. This hypothesis was not supported. Total scores from the NEO PI-R Openness scale were not significantly correlated with su pervisory ratings of creativity at work ( r =.09, n.s .). However, total scores from the NEO PI-R Openness scale did correlate significantly with self-r atings of creativity ( r = .41, p <.01 in the student sample; r = .46, p <.01 in the employee sample). Also, correlation of scores on the Ideas facet with supervisory ratings of creativity approached significance ( r = .21, p <.06). Hypothesis 2. Scores from the Work-specific Openness scale were positively correlated with scores from the NEO PI-R scale of Openness to Experience, so convergent validity for measuring Openness was demonstrated.

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31 Data supported Hypothesis 2 by revealing a strong correlation between total scores on the Work-specific Openness scale and the NEO PI-R Openness scale in the student sample ( r =.65, p <.01) and the employee sample ( r =.72, p <.01). Furthermore, at the facet level there is convincing evidence of convergent validity. Using a multi-trait multi-method matrix in which the facets of Openness are considered as traits, and the two scales (Work-specific and NEO PI-R) are co nsidered methods, significant correlations between corresponding facet scores for the Work-specific scale and the NEO PI-R scale were observed (correlations for the employee sample are included in Table 4). In most cases, discriminant validity is also shown through lower correlations between different facet scores from the same Openness scale, as compared to correlations between the corresponding facets from the two separate (Work-specific and NEO) scales. In the student sample, similar results were f ound and can be seen in Table 3. Hypothesis 3. Facets of Openness from each of the Openness scales differ in their ability to predict creativity in this job domain in the following manner: Openness to Ideas, to Fantasy, to Actions, and to Aesthetics are better predictors of creativity at work for technical research and development personnel than are Openness to Feelings or to Values. Conclusions regarding Hypothesis 3 are equivocal. Although facets differed in their ability to predict supervisory ratings of employee creativity based on zero order correlations, none of the correlations differed significantly from the others as determined using the Hotelling-Williams test. For predic tion of self-ratings however, several significant differences were found. Additional ly, there were surprises as to which facets were significant predictors of supervisory ratings, based on correlations. Correlations

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32 reveal that the Work-specific facets Fantasy, Values, Ideas, and Actions (in decreasing order of magnitude) were significant predictors of the supervisory rating criterion (Table 5). Work-specific Feelings and Aesthetics were not significant predictors. In fact, contrary to the hypothesis, Aesthetics was the weakest predictor in this sample, whereas Values was an unexpectedly strong predictor. Again, however, the differences were not significant. One possible reason for the lack of significance could be lack of power. The difference in validity coefficients (for supervisory ratings) of the Ideas and Aesthetics facets would become significant if N were increased to approximately 120, assuming the relevant correlations were to remain as they are. For comparison, however, it would take approximately 440 participants for the difference in validity coefficients involving Fantasy and Feelings facets to reach significance, assuming correlations relevant to that calculation were to remain as they are. Al though NEO PI-R facets did not significantly predict supervisory ratings of creativity, the facet Ideas approached significance ( r = .21, p <.06). In a multiple regression the beta weights of the Work-specific facets were expected to differ, approximately following the descending order of hypothesized importance. Although beta weights did differ, standardized weights were in this (descending) order: Values, Fantasy, Feelings, Ideas, Actions, and Aesthetics, with Aesthetics being closer to significance than Actions, but in the negative range. None of the beta weights were significant in the regression, with all six facets considered simultaneously, although Values approached significance ( p < .06). Although some collinearity might be expected due to the fact that all facets measure Openness, the Variance Inflation Indices (VIF) of the facets were acceptable, ranging from 1 to

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33 approximately 2.7. Only the Fantasy and Ideas facets had VIFs larger than 2. To further compare the usefulness of the work-specific facets as predictors, two hierarchical regressions were computed. First, the four facets that were expected to be important predictors of supervisory ratings prior to the study (Ideas, Fantasy, Actions, and Aesthetics from the Work-specific Openness scale) were entered as a block and then the other two facets (Feelings and Values, also from the Work-specific Openness scale) were entered to determine whether their entry significantly increased R2. The increase was not significant ( p =.096). Second, the two facets originally hypothesized as not important predictors (Feelings and Values) were entered first and then the other four facets were entered into the equation to determine whet her their entry significantly increased R2. Contrary to prior expectations, the R2 did not increase significantly ( p =.304; see Table 7). Of course, if the hypothesized “important” predictors are chosen to conform to the significant correlations that were found (e xchange the Values an d Aesthetics facets), different results are found for the regressions. When Ideas, Fantasy, Actions and Values are entered as one block, with Feelings and Aesthetics comprising the other block, no significant increase in R2 is found for the 2-facet block over the 4-facet block ( p =.509), but significant incremental validity is shown for the 4-facet block over the 2-facet block ( p =.038; see Table 8). The variance in supervisory ratings of creativity accounted for by the 4-facet block alone was 13.1%, whereas the variance accounted for by all six workspecific openness facets was 14.6%. It is impo rtant to test these re sults using a different sample before any strong conclusions can be made, because the new selection of facets is based on findings from the current sample.

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34 Using self-ratings of creativity as the criterion, regressions using the originally hypothesized “important” and “not important” predictor blocks were computed. Entry of the originally hypothesized “important” block of four Work-specific facets produced a significant change in R2 ( R2=.636, p <.01), but the addition of the other two facets as a block did not produce a significant change ( R2=.020, n.s. ). Beta weights of all facets except Feelings and Values were significant in the full model, but when only the block of four was used as a model, Actions displayed only a near significant beta weight ( p =.056), whereas the beta weights of the other three facets remained significant. When reversing the order of block entry, the two-facet block did not produce a significant change in R2, but the addition of the four-facet block did increase R2 significantly ( R2=.591, p <.01). The variance in self-ratings of creativity accounted for by the 4-facet block alone was 63.6%, whereas the variance accounted for by all six work-specific openness facets was 65.6% (see Table 9). Table 7 Hierarchical Regression of Hypothesized Blocks of Work-specific Openness Facets onto Supervisory Ratings Model R R Square R Square Change Significance of F for Change Ideas, Fantasy, Actions, Aesthetics .349 .122 .122 .158 Above + Feelings and Values .405 .164 .042 .307 Feelings and Values .301 .091 .091 .085 Above + Ideas, Fantasy, Actions, and Aesthetics .405 .164 .073 .392

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35 Table 8 Hierarchical Regression of Revised Blocks of Work-specific Openness Facets onto Supervisory Ratings Model R R square R square change Significance of F for Change Ideas, Fantasy, Actions, and Values .362 .131 .131 .026 Above + Feelings and Aesthetics .382 .146 .015 .509 Feelings and Aesthetics .160 .026 .026 .354 Above + Ideas, Fantasy, Actions and Values .382 .146 .120 .038 Table 9 Hierarchical Regression Results for Hypothesized Blocks of Work-specific Openness Facets onto Self-Ratings Model R R Square R Square Change Significance of F for Change Ideas, Fantasy, Actions, Aesthetics .798 .636 .636 .000 Above + Feelings and Values .810 .656 .020 .125 Feelings and Values .256 .065 .065 .072 Above + Ideas, Fantasy, Actions, and Aesthetics .810 .656 .591 .000 Regression analyses were also completed for the NEO PI-R Openness scale. As would be expected, given that the total NEO PI-R scale was not a significant predictor of supervisory ratings of creativity and that only the Ideas facet approached significance,

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36 initial entry of the blocked facets Ideas, Aesthetics, Actions and Fantasy did not produce a significant change in R2. Adding Values and Feelings facets to this as a block did not change R2 significantly. None of the beta weight s of individual facets was significant at either stage, including that of the Ideas facet. Similar non-significant results were obtained when the order of block entry was reversed. Using self-ratings of creativity as the criterion, NEO PI-R regression results were quite different from those for supervisory ratings. Entry of the NEO PI-R four-facet block produced a significant change in R2 ( R2=.404, p <.01), but addition of the two-facet block did not. Only the beta weight of the Ideas facet was significant, however. When the order of block entry was reversed, the two-facet block did not produce a significant change in R2, but the addition of the four-facet block did ( R2=.395, p <.01). Hypothesis 4. Life area in which creativity is measured impacts the correlation with Openness. The correlation will be higher when creativity and Openness scores are compared for the same life area and will be lower when compared across life areas. For this study, work-specific Openness to Experience was expected to predict supervisory ratings of creativity at work better than does the NEO PI-R measure of general Openness to Experience. Hypothesis 4 was supported. Whereas the correlation between NEO PI-R Openness (total) scores and supervisory ratings was not significant ( r = .09, n.s .), the correlation between Work-specific Openness (total) scores and supervisory ratings was significant and strong ( r = .32, p <.01). In a simultaneous regression of both of these total scores onto supervisory ratings of creativity, the beta weight of the total Work-specific Openness variable was significant ( Standardized beta = .52, p =.001), whereas that of the

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37 total NEO PI-R Openness variable was not ( Standardized beta = -.281, p =.063). Regressions of Work-specific and NEO PI-R facet scores onto supervisory ratings of creativity show that initial entry of all Work-specific facet scores as a block produces a near significant change in R2 ( R2=.146, p <.06), whereas addition of the NEO PI-R facet scores does not increase R2 significantly. Reversing the en try order, initial entry of NEO PI-R facet scores did not yield a significant change in R2 ( R2=.079, n.s. ), whereas the addition of Work-specific facet scores produced a near significant change ( R2=.144, p< .06; see Table 10). Table 10 Hierarchical Regression of Work-specific and NEO PI-R Openness Facets onto Supervisory Ratings Model R R Square R Square Change Significance of F for Change All Workspecific Facets .382 .146 .146 .055 Above + All NEO PI-R Facets .473 .223 .077 .337 All NEO PI-R Facets .281 .079 .079 .376 Above + All Work-specific Facets .473 .223 .144 .057

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38 Discussion This study focused on two primary questions: (1) Will personality measures demonstrate higher validity if their items spec ifically address the construct within the context of interest rather than in a more general context? and (2) Do facets of a single personality scale differ markedly in their abilit y to predict a criterion? In particular, two measures of Openness to Experience were examined at the scale and facet levels to determine their predictive validities for supervisory ratings of creative performance at work. Context Specificity The measure of Openness specifically tailored to the work context was found to be a valid predictor of supervisory ratings of creativity, whereas the more general measure of Openness was not. This finding is consistent with results of a study by Schmit, Ryan, Stierwalt and Powell (1995) in which school-specific versions of NEO PIR items for the Conscientiousness scale demonstrated greater validity for predicting cumulative GPA among college students as compared to standard non-contextual items. It appears that there is a clear advantage to using items that are specific to the work context for prediction of job performance. Not only did the work-specific scale outperform the general scale in predicting supervisory ratings, it was also a better predictor of self-ratings. This suggests that work-specific scales of personality should be

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39 used over more general scales in applied settings, as their context specificity appears to increase their validity for pred iction of important criteria. Differential Validity of Facets An examination of evidence regarding whether facets differed significantly in their predictive ability was inconclusive. A lthough some work-specific facets were significant predictors of supervisory ratings and others were not, the differences between these validity coefficients were not significant. It may be the common or shared variance (the factor underlying the six facets, rather than their differences) that is important for predicting supervisory ratings. Because one possible reason for the lack of significance could be lack of power, research with larger samples might clarify this. As previously mentioned, results from Paunonen and Ashton (2001) showed that theory-based selection of facets may be useful. Recall that their study, mentioned earlier, showed incremental validity of expert-selected facet scores over broader factor scores. For the Work-specific scale, the pattern of zero order correlations at the facet level was similar for prediction of both supervisory and self ratings, with Ideas and Fantasy being quite predictive, Actions slightly less predictive, and Feelings somewhat less predictive (Table 5). Ideas, Fantasy an d Actions were significant predictors for both criteria. However, Values and Aesthetics fa cets differed in predictive ability, depending on rating source. Whereas Values appeared (but was not significantly) more important than Aesthetics for predicting supervisory ratings, just the reverse was true (and significantly so) for predicting self-ratings of creativity at work. Feelings and Aesthetics were significant predictors of self-ratings only, whereas Values was a significant predictor of supervisory ratings only.

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40 The unexpected importance of Openness to Values is particularly interesting in light of evidence that diversity and the presence of dissent in work groups can lead to greater creativity and innovation by the group (De Dreu & West, 2001; Nemeth, Rogers, & Brown, 2001). The significance of Openness to Values is consistent with the idea that challenging norms and being open to diverse viewpoints contributes to creative performance. Although no relationship was found between scores of general openness as assessed by the NEO PI-R and supervisory ratings of creativity, relationships were shown with self-ratings of creativity. Interestin gly, these relationships seemed to follow hypothesized patterns more closely than did the relationships with supervisory ratings. This was true for both the NEO PI-R and Wo rk-specific scales. Perhaps it seems intuitive to us that creativity should “ go with” aesthetics, so people tend to answer these types of questions somewhat similarly whereas values and creativity concepts are not as closely related in our conceptual networks. This difference in “what goes with what” may influence the correlations for self-reports. It is clear that in this study, facets such as Openness to Values (challenging accepted norms, valuing diversity, etc.) better predicted supervisory ratings of creativity than did aesthetics. Prediction of Other Criteria On the criterion side, the correlation be tween supervisory and self ratings of creativity was nearly significant, but not strong ( r =.216, p <.06). In general, self-ratings were more strongly predicted by Openness scores than were supervisory ratings, presumably due to common method variance.

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41 Both creativity and technical proficiency seem to have been considered by supervisors in their ratings of overall job performance, as evidenced by correlations between each of these criteria and overall ratings. However, creative performance and technical proficiency appear to be separate constructs for these technical jobs, as the two criteria were not significantly correlated. When validities for predicting the one-item overall work performance rating or the one-item technical proficiency rating are examined, Openness totals are not significant predictors. Of course, this finding must be interpreted with great caution considering reliability problems with one-it em measures, as well as restricted ranges (ceiling effects) of these two criterion ratings. Nevertheless, this finding is in line with much previous research that has examined valid ities of the Big Five at the trait level. A mix of positive and negative facet-level validities could decrease predictive validity when scores are considered only at the total scale level. This mixture effect does not appear important enough here to explain the weak validity of general openness for prediction of overall performance ratings. However, a closer look at validity of specific facets from the Big Five may be needed for development of more comprehensive theories about predictors of work performance. Rather than using one trait such as Conscientiousness to predict job performance, perhaps selecting facets from several traits depending on which aspects of performance are most essential for the job category is advisable. Precisely because “job performance is complex and multidimensional” (Hogan & Roberts, 1996), it may be time to attempt prediction of several key aspects of performance in particular types of jobs through the use of a combination of more narrow (facet) predictors, rather than single factor pr edictors or one broad personality me asure that includes everything

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42 that may be relevant for any type of job. In this way, a better match of criterion with predictor may be obtained, thus enhancing validity (Hogan & Roberts, 1996). Additional Comments Of some concern is whether Openness measures assess intellect, in which case supervisory ratings might be expected to correlate with Openness because of a relationship between general cognitive ab ility and performance. Because the primary criterion measure used in this study focuses our attention on people who have demonstrated creative effectiveness, the following questions raised by Barron and Harrington (1981, p.455) are important ones: “Which of these “core” personality characteristics facilitate effective social beha vior of almost any form? Which specifically facilitate creative behavior?” (emphasis in original) These questions were posed in reference to a long list of adjectives in the Composite Creati ve Personality scale (Harrington, 1975) from Gough’s Adjective Check List. The adjectives are meant to differentiate between more and less creative individuals, and have been shown to do so when comparing individuals on creative effectiveness. But the concern is that creativity may be confounded with effectiveness. It seems likely that adjectives most closely aligned with Openness to Experience such as ‘artistic’, ‘imaginative’, ‘interests wide’, ‘reflective’ and ‘unconventional’ are likely to enhance creative efforts specifically. These concepts are tapped by many of the Openness items in the scales that were administered in this study. Adjectives that appear to measure certain other personal characteristics such as extraversion, conscien tiousness, and cognitive ability have a more global influence on effectiveness. Examples of these would be ‘ambitious’, ‘clear thinking’, ‘confident’, ‘enthusiastic’, and ‘intelligent’. The current study may aid in

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43 separating predictors of creativity and effectiveness in a variety of areas. The finding of Work-specific Openness to Ideas as the only facet approaching significance as a predictor of supervisory ratings of overall job performance may indicate that this facet is more indicative of effectiveness than are other face ts. A difficulty with this conjecture arises from the observation that the Ideas facet did not predict ratings of technical competency. A general predictor of effectiveness would be expected to predict this criterion also. Nevertheless, additional studies might be he lpful in testing the hypothesis that the Openness to Ideas facet predicts general effectiveness. Clifford, Boufal, and Kurtz (2004) found that Openness scores from the NEO PI-R provided incremental validity, above measures of cognitive ability, for the prediction of critical thinking. Studies that include results for personality at the facet level, as in the current study, but also include measures of cognitive ability might reveal differential relationships between intellect and personality facets. Directions for the Future Just as a relevant job analysis is needed to determine the knowledge, skills, and abilities that should be assessed for selec tion, creativity on the job likely has multiple predictors. It is important to consider the kinds of personal attributes necessary for individuals to produce creative products in a particular area or domain. For the sample of technical personnel in this study, Openness to Experience was hypothesized to be a relevant personal attribute. For team members and those who must gain others’ acceptance for their concepts before implemen tation, predictors of certain social skills may be critical components. As champions of their own ideas, individuals’ personality characteristics such as low anxiety (a neuroticism facet) and moderate assertiveness (a

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44 facet of extroversion) may facilitate commun ication of ideas and persuasive efforts. Extraversion may predict creative achievement differentially for different creative fields, depending on the required amounts of social interaction and introspection necessary to create or innovate within the field (Rank, Pace, & Frese, 2004). Further research is needed on a wide range of personality constructs and their relationships with creative performance. Selection of facets of these personality constructs may help us customize measures that will capture the necessary personal attributes for the particular domain. For example, data from this study indicates that Openness to Fantasy is a significantly predictive facet for creativity at work in this sample whereas Openness to Fe elings is not. But perhaps Openness to Feelings would significantly predict artistic creativity. Further research ma y lead to discovery of the combination of facets of Openness and other personality factors most relevant to creative productivity in a particular type of job. Achievement Striving has been shown by a number of researchers to be positively correlated with creative production (Feist, 1999). Conscientiousness as a whole, however, has often been shown to correlate negatively with creative behavior, particularly when environmental factors encourage rule following and conformity (Feist, 1999; George & Zhou, 2001). Perhaps if Conscientiousness were measured among employees using the NEO PI-R or a more work-specific measure, the Achievement Striving facet would be found to correlate positively with creativity whereas some of the other facets might correlate negatively with creativity. Both negatively and positively correlated facets might be useful in a regression equation as predictors of creative production. Understanding the importance of different personality

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45 facets would enable composite personality measures to be constructed for prediction of creative potential in certain job areas. As Feist insisted (1999, p. 290), “The creative personality does exist and personality dispositions regularly and predicta bly relate to creative achievement in art and science.” Although we have a long wa y to go before we fully understand the personality characteristics that are most predic tive in each field, and the optimal way to measure them, this study provides one piece of the emerging puzzle. The use of predictor measures that match the context of the criterion, along with more specific identification and use of predictor facets that are conceptually related to criteria such as job-specific aspects of creative performance, may greatly help to improve the validity of personality tests and to enrich our understanding of creative achievement.

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46 References Amabile, T.M. (1996). Creativity in context Boulder, CO.: WestviewPress. Baer, J. (1998). The case for domain specificity of creativity. Creativity Research Journal, 11, 173-177. Barron, F. (1988) Putting creativity to work. In R. Sternberg (Ed.), The Nature of creativity: Contemporary psychological perspectives. Cambridge, UK: Cambridge University Press. Barron, F. & Harrington, D.M. (1981). Creativ ity, intelligence, and personality. In M. Rosenzweig & L. Porter (Eds.), Annual review of psychology, 32 Palo Alto, CA: Annual Reviews. Clifford, J.S., Boufal, M.M., & Kurtz, J.E. (2 004). Personality traits and critical thinking skills in college students: Empiri cal tests of a two-factor theory. Assessment, 11, 169-176. Costa, Jr., P.T & McCrae, R.R. (1992). Revised NEO Personality Inventory and NEO Five-Factor Inventory Professional Manual. Odessa, FL: Psychological Assessment Resources. Csikszentmihalyi, M. (1999). Implications of a systems perspective. In R. Sternberg (Ed.), Handbook of creativity. Cambridge, UK: Cambridge University Press. De Dreu, C.K.W. & West, M.A. (2001). Minority dissent and team innovation: The importance of participation in decision making. Journal of Applied Psychology, 86, 1191-1201. Farr, J.L. & Ford, C.M. (1990). Individual innovation. In M. West & J. Farr (Eds.), Innovation and creativity at work: Psychological and organizational strategies. Chichester, UK: Wiley. Farris, G.F. (1981). Groups and the informal organization. In R. Payne & C. Cooper (Eds.), Groups at work. Chichester, UK: Wiley.

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47 Feist, G.J. (1999). Influence of personality on artistic and scientific creativity. In R. Sternberg (Ed.), Handbook of creativity. Cambridge, UK: Cambridge University Press. Frese, M. (2000). The changing nature of work. In N. Chmiel (Ed.), Introduction to Work and Organizational Psychology. Oxford, UK: Blackwell. Gardner, H. (1989). To open minds: Chinese clues to the dilemma of contemporary education. New York: Basic. George, J. M. & Zhou, J. (2001). When openness to experience and conscientiousness are related to creative behavior: An interactional approach. Journal of Applied Psychology, 86, 513-524. Harrington, D.M. (1975). Effects of explicit instructions to “be creative” on the psychological meaning of divergent thinking test scores. Journal of Personality, 43, 434-454. Helson, R. (1996). Arnheim Award Address to Division 10 of the American Psychological Association: In search of the creative personality. Creativity Research Journal, 9, 295-306. Hogan, J. & Roberts, B.W. (1996). Issues and non-issues in the fidelity-bandwidth tradeoff. Journal of Organizational Behavior, 17, 627-637. King, Walker & Broyles, (1996). Creativity and the five-factor model. Journal of Research in Personality, 30, 189-203. King, N. (1990). Innovation at work: the resear ch literature. In West, M.A. & Farr, J.L. (Eds.) Innovation and Creativity at Work: Psychological and organizational strategies. Wiley: Chichester, UK MacKinnon, D.W. (1978). In search of human effectiveness. Buffalo, NY: Creative Education Foundation. McCrae, R.R. (1993-94). Openness to experience as a basic dimension of personality. Imagination, Cognition and Personality, 13, 39-55. Nemeth, C.J., Brown, K.S., & Rogers, J. (2 001). Devil’s advocate versus authentic dissent: Stimulating quantity and quality. European Journal of Social Psychology, 31, 1-13. Nickerson, R.S. (1999). Enhancing creativity. In R. Sternberg (Ed.), Handbook of Creativity. Cambridge, UK: Cambridge University Press.

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48 Nunnally, J.C. & Bernstein, I.H. (1994). Psychometric theory (3rd ed.) New York: McGraw-Hill. Paunonen, S.V. & Ashton, M.C. (2001). Big fi ve factors and facets and the prediction of behavior. Journal of Personality and Social Psychology, 81, 524-539. Pedhazur, E.J. (1997). Multiple regression in behavioral research (3rd ed.). Fort Worth, TX: Harcourt Brace College Publishers. Piirto, J. (1992). Understanding those who create. Dayton, OH: Ohio Psychology Press. Plucker, J.A. (1998). Beware of simple conc lusions: The case for content generality of creativity. Creativity Research Journal, 11, 179-182. Rank, J., Pace, V.L., & Frese, M. (2004). Thre e avenues for future research on creativity, innovation, and initiative. Applied Psychology: An International Review, 53, 518528. Runco, M.A. (1987). The generality of creative performance in gifted and nongifted children. Gifted Child Quarterly, 31, 121-125. Schmit, M.J., Ryan, A.M., Stie rwalt, S.L. & Powell, A.B. (1995). Frame-of-reference effects on personality scale scores and criterion-related validity. Journal of Applied Psychology, 80, 607-620. Sternberg, R.J. & Lubart, T.I. (1999). The concept of creativity: Prospects and paradigms. In R. Sternberg (Ed.), Handbook of creativity. Cambridge, UK: Cambridge University Press. Sternberg, R.J. & O’Hara, L.A. (1999). Creativi ty and intelligence. In R. Sternberg (Ed.), Handbook of creativity. Cambridge, UK: Cambridge University Press. Simonton, D.K. (1988). Creativity, leadership, and chance. In R. Sternberg (Ed.), The nature of creativity: Contemporary psychological perspectives. Cambridge, UK: Cambridge University Press. Tardif, T.Z. & Sternberg, R.J. (1988). Creativity, leadership, and chance. In R. Sternberg (Ed.), The nature of creativity: Contemporary psychological perspectives. Cambridge, UK: Cambridg e University Press. Taylor, C.W. (1988). Approaches to and definiti ons of creativity. In R. Sternberg (Ed.), The nature of creativity: Contemporary psychological perspectives. Cambridge, UK: Cambridge University Press.

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49 Torrance, E.P. (1988). Creativity as manifest in tes ting. In R. Sternberg (Ed.), The nature of creativity: Contemporary psychological perspectives. Cambridge, UK: Cambridge University Press. Walberg, H.G. (1988). Creativity and talent as learning. In R. Sternberg (Ed.), The nature of creativity: Contemporary psychological perspectives. Cambridge, UK: Cambridge University Press.

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50 Appendix A Factor Pattern Matrix in Student Study

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51 Item Component 1 2 3 4 5 6 q159 .702 .070 .116 -.121 .119 -.056 q76 .617 .072 -.024 -.042 -.279 .175 q72 .541 -.026 -.024 .194 -.101 .049 q146 .506 .343 -.112 -.151 .088 -.010 q189 .503 -.020 -.148 -.063 -.026 .059 q109 .479 .205 -.065 .069 .077 -.014 q242 .451 -.234 .107 -.160 .258 .273 q226 .445 -.036 -.088 .288 .167 .195 q164 .428 -.039 .076 .043 .177 .172 q128r -.155 .586 .133 .114 -.132 .039 q100 .094 .580 -.070 .084 .120 -.042 q60 .102 .553 .153 .089 -.025 -.118 q173 -.083 .541 -.419 .211 .060 -.063 q134 .004 .469 -.176 -.076 .397 -.034 q115r .287 .413 .311 .301 -.247 -.195 q237r .024 .407 .254 .101 .096 .284 q138 .271 .403 -.193 -.201 -.151 .357 q130r -.077 .386 -.211 .302 -.086 .218 q157 .122 .386 -.016 .029 .334 -.044 q167 .143 .374 -.301 .055 .070 .018 q190 -.286 .350 -.183 .348 .316 -.059 q243r .245 -.027 .651 .120 -.083 .053 q154r .025 -.019 .648 .153 .041 -.129 q178r -.177 .095 .603 -.068 .092 .086 q162r -.124 -.086 .577 .087 .294 .165 q247r -.325 .264 .465 .099 -.080 .263 q187 .385 .212 .429 .113 .253 -.288 q181 -.039 .159 -.404 .094 .119 -.014 q192r -.353 .087 .396 .090 .058 .192 q79r .069 .050 .301 .682 -.051 -.006 q140 .164 .184 -.159 .606 -.311 -.010 q97r -.134 .082 .175 .593 .242 .037 q195r -.037 -.020 .158 .588 -.033 .316 q194 -.067 .168 .007 .564 .092 -.063 q124 .012 -.241 -.265 .450 .416 .059 q118 .168 .119 -.202 .336 .103 -.035 q46 -.088 .032 .031 -.094 .666 -.099 q25 .297 -.037 .105 .092 .590 .069 q182 -.090 -.057 .092 .409 .517 -.084 q142 .045 .437 .366 -.127 .475 -.035 q88 .114 .278 -.028 .013 .394 -.004 q183r .226 -.281 .047 .063 .000 .669 q186r .024 -.142 .270 .233 -.234 .556 q180r -.206 .266 .268 -.117 -.066 .527 q228 -.411 -.033 .027 -.119 .173 -.514 q238 .258 .025 -.125 .024 .281 .455 q244 -.036 .071 -.386 .122 .028 .403 q163r .135 .316 .023 -.273 .158 .393 Extraction Method: Principal Component Analysis. Rotation Method: Promax with Kaiser Normalization.

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52 Appendix B Work-Specific Openness Scale

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53 Ideas 60. I find tricky problems more enjoyable than simple ones. 100. I like to think about different ways to structure work groups. 118. I am curious about competitors' ideas. 130. Extremely unusual ideas are seldom worth considering. (R) 142. I get ideas for work solutions from seemingly unrelated knowledge and situations. 167. I am very interested in what people in other departments and other firms are doing. 173. I like to hear about how others develop their ideas. 190. I like training in new ways of working. Values 162. ‘If it ain't broke, don't fix it’ is a good motto. (R) 180. I think American business practices should be applied everywhere in the world. (R) 186. I have a hard time understanding why other people in similar jobs to mine do things differently than I do. (R) 192. I believe everyone in the company should share the same vision of the direction for development. (R) 195. I think people who want to change the workplace would probably be better off finding a different workplace. (R) 237. Making changes to a system that works is a bad idea. (R) 243. It is best to rely on supervisors for most work decisions. (R) 247. I think it is best if people who wo rk together are very similar. (R) Aesthetics 72. The visual appeal of my work area is important to me. 109. I consider aesthetics important in my work. 124. I get a great deal of pleasure from creating beautiful things. 146. The form my work takes is just as important to me as its function. 164. I expect my work to please the senses. 182. I take great pains in putting on th e finishing touches to my work. 226. I focus on making my work attractive to others. 238. For me, artistic considerations make the difference between good and great work products. Fantasy 25. I am very imaginative at work. 46. I come up with involved fantasies about work projects and situations. 88. When I am considering job solutions, I like to follow very unusual thoughts to see where they might lead. 134. Sometimes I think at length about the wildest product concepts, expanding upon them in my imagination.

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54 Appendix B (Continued) 157. I can visualize in great detail what a product might look like before it has been made. 163. I think spending time fantasizing about projects is a waste of effort. (R) 181. I spend a lot of time dreaming about how things might be. 187. I can imagine how something might work without seeing it. Feelings 76. Different work environments affect my mood for better or worse. 138. I like to choose tasks and organize my work to fit my varying moods. 159. I sometimes feel strong emotions about my work. 183. To me, there is no place for feelings at work. (R) 189. Positive or negative feedback about my work can have a real effect on how I feel. 228. I seldom notice how work tasks make me feel. (R) 242. I experience many different emotions at work. 244. I am usually aware of my mood at work. Actions 79. I prefer to stick with job tasks I do well rather than to try new tasks. (R) 97. I use familiar paths within the workplace rather than exploring other areas. (R) 115. I prefer to work on simi lar tasks each day. (R) 128. I tend to use the same techniques on each project. (R) 140. I like a lot of variety in my job. 154. I have structured routines I like to follow. (R) 178. I believe in finding a formula for success and using it consistently. (R) 194. I like jobs with tasks that change frequently. Note: Item numbers correspond to Student Study administration.

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55 Appendix C Sample NEO PI-R Op enness Scale Items

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56 Fantasy I have an active fantasy life. I don’t like to waste my time daydreaming. (R) Aesthetics Aesthetic and artistic concerns aren’t very important to me. (R) I am sometimes completely absorbed in music I am listening to. Feelings Without strong emotions, life would be uninteresting to me. Actions I’m pretty set in my ways. (R) Sometimes I make changes around the house just to try something different. Ideas I often enjoy playing with theories or abstract ideas. Values I believe letting students hear controversial speakers can only confuse and mislead them. (R) I consider myself broad-minded and tolerant of other people’s lifestyles.

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57 Appendix D Supervisory Rating Form

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58 Rating Form Target ID____________ Please circle the number at the right that best expresses your view of the employee.Strongly Disagree Not Agree Strongly Disagree Sure AgreeIn your observations, this employee: 2)Producesalargerquantityofinnovativeideasthan other employees do. 1 2 3 4 53) Produces very unique and useful high quality work. 1 2 3 4 54) Has very original ideas. 1 2 3 4 55) Is among the first employees I would approach if I needed an innovative solution for a work project. 1 2 3 4 56) Proposes exceptionally creative work solutions. 1 2 3 4 57) Performs technical tasks with competence, is accurate in own work, avoids mistakes/errors, and produces sound products. 1 2 3 4 58) How long have you been this employee's supervisor? _________________ Your e-mail address (optional, only to be used if clarification is needed): ________________________ Very Ineffective Effective Very Effective 1) This employee's overall job performance is: (please circle number) 1 2 3 4 5

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59 Appendix E Boxplots for Predictor and Criterion Variables

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60 Figure E1 Boxplots for Work-specific a nd NEO PI-R Openness Totals wkopentotneoopentot 120.00 140.00 160.00 180.00 200.00 220.00 16

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61 Appendix E (Continued) Figure E2 Work-specific Openness Facet Scale Boxplots (L to R: Values, Fantasy, Aesthetics, Feelings, Actions, and Ideas) wkvaluesavg wkfa n ta sya v g wkae st he t i csa v g wkfeeli n g s avg wkact i o n sa v g wki d e a savg 1.00 2.00 3.00 4.00 5.00 32 31 6347 63 16 78 65 60 59 65

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62 Appendix E (Continued) Figure E3 NEO PI-R Openness Facet Scale Boxplots (L to R: Values, Fantasy, Aesthetic s, Feelings, Actions, and Ideas) ne o va l ue s av g ne o f a ntasyavg ne o ae sthe t i c s av g ne o f e elingsavg ne o ac t i o ns a vg neoi d ea s avg 1.00 2.00 3.00 4.00 5.00 15 21 29 65 54 63

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63 Figure E4 Supervisory Creativi ty Rating Boxplot supcreat 2.00 2.50 3.00 3.50 4.00 4.50 5.00 Figure E5 Self-rated Creativity Boxplot slfcreat 2.00 2.50 3.00 3.50 4.00 4.50 5.00 63 30 61

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64 Appendix E (Continued) Figure E6 Overall Performance Rating Boxplot overall performance 2.0 2.5 3.0 3.5 4.0 4.5 5.0 16 Figure E7 Technical Proficiency Rating Boxplot technical competency 2.0 2.5 3.0 3.5 4.0 4.5 5.0 75