self-regulation of creativity at work: the...

SELF-REGULATION OF CREATIVITY AT WORK:THE ROLE OF FEEDBACK-SEEKING BEHAVIOR IN

CREATIVE PERFORMANCE

KATLEEN E. M. DE STOBBELEIRVlerick Leuven Gent Management School

SUSAN J. ASHFORDUniversity of Michigan

DIRK BUYENSVlerick Leuven Gent Management School

andGhent University

Using 456 supervisor-employee dyads from four organizations, this study examinedhow employees use one proactive behavior, feedback seeking, as a strategy to enhancetheir creative performance. As hypothesized, employees’ cognitive style and perceivedorganizational support for creativity affected two patterns of feedback seeking: thepropensity to inquire for feedback and the propensity to monitor the environment forindirect feedback. Feedback inquiry related to supervisor ratings of employee creativeperformance. These results highlight the importance of employees’ self-regulatorybehaviors in the creative process and show that feedback seeking is not only a strategythat facilitates individual adaptation, but also a resource for achieving creativeoutcomes.

In the past decade, considerable research effortshave identified and described the individual andcontextual factors that facilitate and hinder em-ployees’ creative performance at work (see Shalley,Zhou, and Oldham [2004] for a review). Creativeperformance, defined as the extent to which em-ployees generate novel and useful ideas regardingprocedures and processes at work (Oldham & Cum-mings, 1996; Shalley, 1991), has been examined asa function of individual differences, features of thecontext surrounding employees, and the interac-tion between the two (Shalley & Zhou, 2008; Shal-ley et al., 2004; Woodman, Sawyer, & Griffin, 1993).

The majority of work on individual differences increative performance has focused on identifyingthe personality characteristics and traits associatedwith creative outcomes. For example, research hasshown that creative individuals tend to be moreflexible in absorbing information, demonstrablyhigher in levels of intrinsic motivation for creativ-ity, and more open to new experiences. Researcherscontinue to examine new individual differences(e.g., “growth needs strength” [Shalley, Gilson, &Blum, 2009] and “learning orientation” [Gong,Huang, & Farh, 2009]). This literature also suggeststhat managers and organizations can build workenvironments that support employee creativity bysetting creativity work goals, making creativity ajob requirement, providing developmental feed-back on creative goal progress, leading in a “trans-formational” manner, and rewarding employeeswhen they achieve creative outcomes (Amabile &Mueller, 2008; Gong et al., 2009; Paulus, 2008;Shalley, 2008; Shalley & Liu, 2007; Shin & Zhou,2003; Tierney, 2008; West & Richter, 2008; Zhou,2008).

This impressive support for the role of employeetraits and managerial actions in employee creativ-ity suggests that these research traditions should becontinued and expanded. It is surprising, however,

The authors wish to thank Scott Derue, Ned Wellman,Ans De Vos, Maddy Janssens, Marc Buelens, and FrankBelschak for their comments on drafts. We also thankRick Bagozzi and Michael Jensen for their help and feed-back on our data analyses, Manu Dekeuleneer for histechnical assistance in the collection of data, and GordanFoxall and Michael Kirton for their guidance in the use ofthe Kirton Adaptation-Innovation Inventory. The contri-butions of Katleen De Stobbeleir were made possible by ascholarship from the ICM (Interuniversity Centre forManagement Sciences), Belgium.

Editor’s note: The manuscript for this article was ac-cepted during the term of AMJ’s previous editor, DuaneIreland.

� Academy of Management Journal2011, Vol. 54, No. 4, 811–831.

811

Copyright of the Academy of Management, all rights reserved. Contents may not be copied, emailed, posted to a listserv, or otherwise transmitted without the copyright holder’s expresswritten permission. Users may print, download or email articles for individual use only.

that so little is known about the actions employeesthemselves may take to manage and enhance theirown creative performance (Drazin, Glynn, & Kazan-jian, 1999) and how these may also contribute tocreative performance. Understanding how employ-ees increase their own creative performance may beas important as understanding who they are or howtheir context facilitates their efforts. Although re-searchers have proposed that various cognitive pro-cesses occur in creativity (Amabile & Mueller,2008; Drazin et al., 1999; Drazin, Kazanjian, &Glynn, 2008) and that employees behaviorally at-tempt to produce creative outcomes, empirically,little is known about the specific strategies employ-ees use to manage their creative process and howthese strategies may relate to actual creative perfor-mance (Drazin et al., 2008; Ruscio, Whitney, &Amabile, 1998).

The view that employees actively manage theircreative performance is consistent with self-regula-tion theory’s emphasis on individuals’ ability toguide their own goal-directed activities and perfor-mance by setting their own standards and monitor-ing their progress toward these standards (Carver &Scheier, 1981; Vohs & Baumeister, 2004). Self-reg-ulation theory has been applied to a variety oforganizational phenomena, including managerialwork (Ashford & Tsui, 1991; Tsui & Ashford, 1994),employee socialization (Ashford & Black, 1996),and employee performance (Porath & Bateman,2006; VandeWalle, Brown, Cron, & Slocum, 1999).On the basis of self-regulation theory’s demon-strated utility for studying organizational phenom-ena, we believe that it also offers a promisinglens for gaining insights into employee creativeperformance.

One key self-regulation tactic that has been iden-tified is feedback-seeking behavior: individuals’proactive search for evaluative information abouttheir performance (Ashford & Tsui, 1991; Porath &Bateman, 2006). Feedback-seeking behavior may becentral to the creative process for two reasons.First, research has shown that managers can usefeedback to promote and nurture the creative per-formance of employees (Zhou, 2008). However, intoday’s dynamic world of work, where creativityand innovation have become a source of competi-tive advantage (Shalley et al., 2009; Zhou, 1998),organizations may not always be able to systemat-ically predefine and prespecify the goals that em-ployees need to achieve (Ashford, George, & Blatt,2007). Because of the ambiguity accompanying cre-ative work, determining the best managerial inter-ventions for enhancing employees’ creative perfor-mance has become an increasingly intricate task formanagers (Shalley, 2008). For example, the nonrou-

tine character of the creative process means thatmanagers may not provide feedback at the time aperformer desires or needs it. To the extent thatthese factors constrain formal organizational feed-back, today’s organizations become increasinglydependent on employees’ own self-regulation ef-forts to acquire feedback to maximize their creativeperformance.

Second, individuals’ creative performance isthought to be partially the result of a social processin which others in their environment stimulate andsupport creativity (Perry-Smith & Shalley, 2003).As such, individuals both within and outside em-ployees’ immediate work setting are increasinglyimportant contributors to their creative perfor-mance (Madjar, 2005; Madjar, Oldham, & Pratt,2002). Recent research has shown that employees’interactions with those whose expertise and back-grounds differ from their own (e.g., individualsfrom different departments and organizations) arean important source of new ideas (Madjar, 2005;Madjar et al., 2002). Although much has beenlearned from this research, a limitation is that it hasnot specified the content of the information that isexchanged during these interactions. Research inthe information seeking literature has distin-guished five types of information that may be ex-changed during these interactions: task informationabout how to perform specific job activities, roleinformation about the expectations associated witha job, social information about how to behave, or-ganizational information about procedures andpolicies, and performance information about howothers are perceiving and evaluating one’s perfor-mance (Morrison & Vancouver, 2000). All thesetypes of information may be of value to employees’creative performance, and employees may seek allof them. Our focus, however, is on the importanceof performance information, which is also called“feedback,” in enhancing creative performance. AsZhou (2008) highlighted, feedback may be particu-larly conducive to creative performance, becausefeedback reduces some of the uncertainty associ-ated with the changing nature of work and becauseit helps performers to set creative standards. Feed-back may suggest new paths to consider for push-ing work forward and stimulate new ideas for im-proving processes.

We propose that employees’ active seeking offeedback is important, as the various externalsources that potentially contribute to employee cre-ative performance may not always provide theirfeedback spontaneously or at the right time. In-deed, more distant, external sources may not beaware of an employee’s desire for advice and guid-ance (Higgins & Kram, 2001), or they may feel that

812 AugustAcademy of Management Journal

they have no formal authority to provide feedbackand thus may consider not giving it. As such, ac-tively seeking feedback from these sources may bethe only way for performers to obtain this crucialexternal input to enhance their creative perfor-mance. Hence, although managers can use feedbackas a tool to stimulate and foster creative perfor-mance (Zhou, 2008), the above realities suggestthat feedback seeking may be a valuable resourcefor employees in managing their own creativeperformance.

Considering individuals’ attempts to enhancetheir own creative performance through feedbackseeking expands thinking about this phenomenonbeyond a focus on adaptation and individual con-formance to the demands of an organization (Ash-ford & Black, 1996; Parker & Collins, 2010) that isdominant in the literature. Research in this domi-nant view has shown that feedback seeking enablesindividuals to adapt and respond to continuouslychanging goals and role expectations (Morrison &Weldon, 1990; Tsui & Ashford, 1994), obtain moreaccurate self-views (Ashford & Tsui, 1991), im-prove their task performance (Chen, Lam, & Zhong,2007), and learn the ropes of a new job (Ashford &Black, 1996; Morrison, 1993). Feedback seeking inthis view is a strategy used to achieve better fit withan environment. This dominant view fits the tenetsof self-regulation theory (e.g., Carver & Scheier,1981), yet it does not entirely reflect Ashford andCummings’s (1983) original portrayal of feedbackseekers or further theorizing by Tsui and Ashford(1994). Ashford and Cummings (1983) describedfeedback seekers as proactive and self-determinedcontributors who can and do set their own stan-dards and seek feedback to achieve personalgoals—not solely as individuals who await social-ization by others and seek feedback to better live upto the expectations of others. Tsui and Ashford(1994) noted that feedback is simply informationabout “the self” and contended that this informa-tion can stimulate a variety of responses, includingattempting to influence rather than conform to theviews held by the feedback givers. Despite thesetheoretical suggestions, however, in summarizing20 years of research on feedback seeking, Ashford,Blatt, and VandeWalle commented that “the gen-eral tone of feedback-seeking literature has beenone of seeking to survive, to fit in, and to tailoroneself to the prevailing view held by others in theorganization” (2003: 794).

In jobs in which being creative is an explicit jobdemand, the adaptation perspective is adequate toexplain feedback seeking’s effects. However, feed-back-seeking behavior can also enhance creativeperformance in jobs in which it is not an explicit

job demand. Feedback seeking increases theamount and diversity of input performers haveabout their work. We propose that this input canserve as an important stimulus to creative perfor-mance. Thus, this study contributes to both thecreativity and feedback seeking literatures by em-phasizing how feedback seeking can help individ-uals to attain outcomes beyond adaptation that pro-mote creativity and innovation in organizationsand by showing how individuals can enhance theircreative performance through their self-regulatoryefforts. Specifically, we develop and test a model,shown in Figure 1, that integrates and extends pre-vious creativity research by simultaneously consid-ering individual traits and context factors as ante-cedents of creative performance and by testingwhether feedback-seeking behavior is an underly-ing mechanism through which these antecedentsaffect creative performance. Our findings add to thegrowing literature on individual differences andcontext factors as predictors of creative perfor-mance in suggesting that individuals’ behaviorsmay have an influence as well.

THEORY AND HYPOTHESES

Feedback-Seeking Behavior andCreative Performance

Ashford and Cummings (1983) proposed that em-ployees can seek feedback using either the tactic ofinquiry, which involves direct verbal requests forperformance evaluations, or the more covert tacticof monitoring, which involves examining their en-vironment for indirect feedback cues. With inquiry,individuals seek input into their performance bydirectly asking others for feedback. For example,employees may deliberately choose to ask a num-ber of sources for feedback, because it may helpthem to get new and different insights into theirwork. With monitoring, individuals observe theirown task progress and the actions of those aroundthem to gain insights into aspects of their perfor-mance (Ashford & Cummings, 1983). Research hasshown that although these feedback-seeking behav-iors (particularly monitoring) may be subject to per-ceptual biases, individuals can increase their over-all effectiveness by inquiring for direct feedbackand monitoring their environment for indirect cues(Ashford & Tsui, 1991). We propose that individu-als can also use these two tactics to attain creativeoutcomes.

This suggestion may seem counterintuitive.Feedback seeking is often portrayed as reactive andconservative, and frequent feedback seekers as re-active, other-dependent, worried about what others

2011 813de Stobbeleir, Ashford, and Buyens

think, and unable to think on their own. Ashfordand colleagues, however, have argued that feed-back seeking is not inherently reactive or conserva-tive. Indeed, both Grant and Ashford (2008) andParker and Collins (2010) included feedback seek-ing as one of several proactive strategies. They por-trayed it as a strategy people use to get ahead ofdemands that is available to individuals interestedin taking control of their own destinies in organi-zations. Tsui and Ashford (1994) wrote about feed-back seeking as a valuable resource when a job isambiguous and involves multiple constituencies(e.g., managerial work). They proposed feedbackseeking as a way for an individual to understandhow constituents are viewing his/her performance.They theorized that people can then use that feed-back information in a variety of ways; they may, forexample, use it to conform to constituents’ views orto engage in persuasion to help them to changetheir views (e.g., Tsui, Ashford, St. Clair, & Xin,1995). Prior empirical research has mainly focusedon feedback seeking in the service of fitting in, ofadapting to a setting. The question of whether feed-back seeking about one’s performance can also con-tribute to dynamic and creative processes and per-formances remains open.

Seeking Frequency and EmployeeCreative Performance

Building on research highlighting the importancein the creative process of feedback given to a per-former (Zhou, 2008), we expect that individuals’efforts to seek feedback actively will also contributeto their creative performance. Feedback seeking issimply an agentic means for employees to get feed-back (and its benefits) more often, on their ownschedule, and on the basis of their needs. Thoughno studies have explicitly linked employees’ feed-back-seeking behaviors to creative performance,the logic for such a relationship is as follows: Directverbal feedback gives a clear picture of how otherssee the employees’ work and ideas, thereby facili-tating subsequent adjustments and improvementsto the ideas.

A habit of frequent feedback seeking, even if from(in the extreme) a single source, or target, brings aperformer in contact with that target’s view on his/her work, maintains that contact as those viewsperhaps shift over time in response to changingconditions, and can provide differing perspectivesthat help the performer make new creative linksthat are relevant for his/her work. Essentially, we

FIGURE 1Structural Modela

C3

.70 .70 .76

.43e

I1 I2 I3

.50

.23e

I4

P2

.21e

P3

P1

.59

C1

C2

S1

S2

S3.27e

.69

.75

.61

.84

.86

.82

.21**

.17*

.27**

.33e

.29e

.61e

.41e

.55e

.32e

Feedback Inquiry R² = .33

Creative Performance R² = .13

Cognitive Style .32**

.35**

POS for Creativity

Feedback Monitoring R² = .12

M1 M2 M3

.55

.28e

.49e

.26e

.28e

.31e

.20**

.22*

.06

.52 .46 .53

.48e

a The path coefficients represent the standardized parameter estimates for the mediated structural model that we tested in SEM. “POS”is “perceived organizational support.”

* p � .05** p � .01

Two-tailed tests.


propose that people who seek feedback on theirperformance more frequently hear more views thatmay clash with their own (or clash with eachother). Deciding how to respond to those clashesstimulates creativity.

Employees do not always need to communicatewith others to obtain such input, however. Indeed,research conducted from a social cognitive per-spective has shown that individuals can learn tothink and behave creatively by observing and mon-itoring creative models (Shalley & Perry-Smith,2001; Zhou, 2003). In doing their jobs, individualsmay make observations of how others proceed intheir work or how others act and react toward themand their work. These observations can serve asfeedback on their own work and work processes(Ashford & Cummings, 1983) and may stimulatemore divergent thought as an input to creative per-formance. Monitoring for feedback in this mannermay be an attractive strategy, as individuals canobtain feedback on their work and make adjust-ments without revealing their desire for the infor-mation. Thus they can obtain feedback without the“image costs” associated with directly asking for it(Larson, 1989; Northcraft & Ashford, 1990). If indi-viduals are being creative in their work by tryingout new ideas or processes, attending to these moreindirect cues in the environment through monitor-ing may be especially attractive, as the data areoften readily available in the actions and reactionsof others, and performers can get the feedback theyneed to further refine their nascent new ideas with-out exposing themselves to some of the potentialimage costs associated with inquiring for feedback.

Thus, feedback information, whether obtaineddirectly via inquiry or indirectly via monitoringcognitively stimulates individuals to think outsideof the box, consider alternatives, and generate moreideas (Madjar, 2005). The more frequently perform-ers seek, the more data they have upon which tobase creative responses:

Hypothesis 1a. Employees’ feedback-seekingbehavior affects creative performance: Feed-back inquiry frequency is positively related tocreative performance.

Hypothesis 1b. Employees’ feedback-seekingbehavior affects creative performance: Feed-back monitoring frequency is positively relatedto creative performance.

Seeking Breadth and Creative Performance

Just as more frequent feedback seeking may en-hance creative performance, seeking broadly acrossdiverse sources may also do so. Researchers have

focused primarily on employees’ feedback sourcepreferences (e.g., Ashford & Tsui, 1991) and on thesource characteristics that influence these prefer-ences (e.g., Levy, Cober, & Miller, 2002; Vancouver& Morrison, 1995; Williams, Miller, Steelman, &Levy, 1999). For example, Ashford and Tsui (1991)found that managers tend to seek more feedbackfrom supervisors than from peers and subordinates.Exploring the underlying rationale for thesechoices in the laboratory, Vancouver and Morrison(1995) found that several source characteristics, in-cluding their “reward power,” accessibility, andexpertise, trigger feedback seekers’ preferences. Al-though these results highlight that individuals dis-criminate among various feedback sources, the im-pact of an overall propensity to seek feedbackbroadly is unknown. It may be that some individ-uals discriminate among sources on the basis oftheir reward power, accessibility, and expertiseand as a result seek narrowly—from, say, only theirsupervisors. Others may seek more broadly, tap-ping a range of feedback sources. For example, theycan also directly inquire for feedback from imme-diate coworkers, other organizational sources (e.g.,peers in other departments), and extraorganization-al sources (e.g., peers in other organizations) (Ash-ford & Tsui, 1991; Miller & Jablin, 1991; Morrison,1993; Vancouver & Morrison, 1995). Further, usingmonitoring, employees can observe not only thebehaviors of their supervisors to infer a feedbackmessage, but also the behaviors of their peers andeven of peers in other areas and companies as theycome into contact with them through, for example,task forces or industry events. Through direct in-quiry and observing the actions and reactions ofmany people, broad feedback seeking via inquiryand monitoring can yield divergent inputs for aperformer and stimulate the creative process.

This suggestion is consistent with theorizing inthe creativity literature that diverse input andknowledge enhance creative performance (Cohen &Levinthal, 1990; Perry-Smith, 2006, 2008). For ex-ample, drawing on insights derived from the liter-atures on individual cognition (Ohlsson, 1992),brainstorming (Paulus, Larey, & Dzindolet, 2001)and group diversity (Milliken & Martins, 1996),Madjar (2005) theorized that employees who seekinformation more frequently from individualswithin and outside their organizations are morecreative, because of the variety of information andinsights the multiple sources provide. Similarly,individuals who seek feedback about their perfor-mance broadly, whether through inquiry or moni-toring, increase their exposure to potentially differ-ing views about what they should be doing, what isgoing well, what’s important, and so forth. This


diversity of input gives those who seek broadly agreater chance of coming up with creative re-sponses about and inputs into their work.

Building on these suggestions and on the dem-onstrated impact of feedback given by others on thecreative process (e.g., Zhou, 1998; and see Zhou[2008] for a recent review), we hypothesize:

Hypothesis 2a. Employees’ feedback-seekingbehavior affects creative performance:

Feedback inquiry breadth is positively relatedto creative performance.

Hypothesis 2b. Employees’ feedback-seekingbehavior affects creative performance:

Feedback monitoring breadth is positively re-lated to creative performance.

Cognitive Style and Feedback-Seeking Behavior

Not all individuals are equally motivated to usefeedback seeking as a strategy to enhance their cre-ative performance. One variable that may influencethis tendency is an individual’s cognitive style.This variable, indexing individuals’ preferred waysof gathering, structuring, and applying information(Hodgkinson & Sadler-Smith, 2003; Kirton, 1976,1994), has been studied extensively as an anteced-ent of creative performance (Tierney, Farmer, &Graen, 1999; see Shalley et al. [2004] for a review).

Debate exists about the conceptualization andmeasurement of cognitive style (Cools & Van denBroeck, 2007; Hodgkinson & Sadler-Smith, 2003),but Kirton’s (1994, 2003) framework has receivedthe most attention in the creativity literature (Shal-ley et al., 2004). This framework suggests that in-dividuals fall on a continuum anchored by twogeneral orientations: (1) an adaptive style, charac-terized by a pronounced preference for accurateinformation, facts, figures, and conventional theo-ries and procedures, and (2) an innovative style,characterized by a preference for more personalinformation and divergent thinking and problemsolving. Though Kirton’s (1994) theory suggeststhat people at both the adaptive and innovativeends of the continuum can demonstrate equal lev-els of creative performance (though in differentways), empirical work has shown a positive linkbetween an innovative style and creative perfor-mance (e.g., Shalley et al., 2009; Tierney et al.,1999). For example, Tierney et al. (1999) found thatseveral indicators of creative performance werepositively associated with having a more innova-tive style. One limitation of prior studies, however,is that they have not examined why cognitive styleaffects creative performance. Presumably, a more

innovative cognitive style affects creative perfor-mance through its impact on employee behaviorsthat enable this performance (Hodgkinson &Sadler-Smith, 2003). Tierney et al. offered one sug-gestion in this regard, proposing that individualswith a more innovative cognitive style may be morelikely to seek and integrate diverse information andthat this tendency stimulates creative outcomes.

We propose that individuals’ cognitive style notonly affects their creative performance by increas-ing their tendency to seek and integrate informa-tion, but also by increasing their propensity to seekfeedback. More specifically, we expect that indi-viduals with a more innovative style are morelikely to both inquire for feedback and monitortheir environment for indirect feedback cues bothmore frequently and more broadly. By doing so,they increase and diversify their knowledge basesabout their work, which allows them to act more inalignment with their cognitive orientation (i.e., tobe creative).

Our proposal is supported by research showingthat the cognitive style of individuals determinesnot only whether or not they like new information,but also the type of information they prefer (Mc-Kinnel Jacobson, 1993). Kirton (1994) stated thatinnovators’ preference for divergent thinking makesthem more interested in and attuned to informationthat leaves room for it. Supporting this view, re-search has shown that individuals with a moreinnovative style tend to prefer information that re-flects others’ opinions (preferably diverse opin-ions) over facts and figures (McKinnel Jacobson,1993). Although this preference for others’ opin-ions has surface similarities to that held by “highself-monitors” (Gangestad & Snyder, 2000; Snyder,1974), self-monitoring is by definition about con-formity, about being chameleon-like and living upto others’ expectations (Snyder, 1974). It is notsurprising, then, that self-monitoring research hassuggested a negative relationship with creativity(de Vet & de Dreu, 2007). An innovative cognitivestyle, however, is somewhat different. Kirton(1994) defined an innovative cognitive style as anindividual’s preference for redefining posed prob-lems and for generating ideas likely to deviate fromthe norm. Thus, people with such an innovativecognitive style value others’ opinions over factsand figures because these opinions give them ideasor food for thought while still allowing for diver-gent thinking and drawing their own conclusions.Facts and figures stimulate convergent thinking(Houtz, Selby, Esquivel, Okoye, Peters, & Treffin-ger, 2003; Isaksen, Lauer & Wilson, 2003; Kirton,1994), but feedback is just an opinion others holdabout one’s work. Individuals whose styles anchor


the more innovative end of the cognitive style con-tinuum are comfortable in the realm of opinion;they value personal information, even though thisinformation can be biased (Kirton, 1994). By morefrequently and broadly seeking opinions, innova-tors increase their pools of information, but infor-mation that still allows for personal interpretationand the divergent views that fit with their style’spreference for divergent thinking.

Individuals with styles on the more adaptive endof the continuum prefer convergent thinking(Gryskiewicz & Tullar, 1995; Kirton & de Ciantis,1986). As such, they tend to be more attuned to datathat provide them with unbiased information onwhat is right and what is wrong (Gryskiewicz &Tullar, 1995). Individuals with more of an adaptivestyle tend to have a preference for unbiased, imper-sonal, and factual information (Houtz et al., 2003).Given this preference and the tendency of individ-uals with more adaptive styles to be less sociallyengaged (Isaksen et al., 2003; Jacobson, 1993), theymay prefer feedback from their task or objectivemonitors of performance rather than others’ opin-ions. Such impersonal, objective feedback may notcontribute to creative performance. Accordingly,we expect that the more innovative an individual’scognitive style, the more he or she will be inter-ested in others’ feedback and will try to acquire thisfeedback by actively monitoring the environmentand directly and frequently asking a broad range ofsources for feedback.

Hypothesis 3a. Employees’ cognitive styles af-fect their general propensity to seek feedback:The more individuals exhibit an innovativecognitive style, the more frequently they in-quire for feedback.

Hypothesis 3b. Employees’ cognitive styles af-fect their general propensity to seek feedback:The more individuals exhibit an innovativecognitive style, the more frequently they mon-itor for feedback.

Hypothesis 3c. Employees’ cognitive styles af-fect their general propensity to seek feedback:The more individuals exhibit an innovativecognitive style, the more broadly they inquirefor feedback.

Hypothesis 3d. Employees’ cognitive styles af-fect their general propensity to seek feedback:The more individuals exhibit an innovativecognitive style, the more broadly they monitorfor feedback.

Perceived Organizational Support for Creativityand Feedback Seeking

Building on theory and research suggesting theview that supportive contexts encourage both em-ployee creative performance (see Shalley et al.[2004] for a review) and feedback-seeking behavior(Ashford et al., 2003), we expect that employees’tendency to seek feedback to enhance their creativeperformance will in part be determined by theirperceptions of their organizational context. We fo-cus on perceived organizational support for creativ-ity, which refers to employees’ perceptions of theextent to which their organization stimulates, re-spects, rewards, and recognizes creativity (Scott &Bruce, 1994; Zhou & George, 2001). Perceived or-ganizational support for creativity is also some-times called “climate for creativity” (Scott & Bruce,1994). Perceived organizational support for creativ-ity has already been identified as a direct anteced-ent of employee creative performance (Zhou &George, 2001). Little is known, however, about themechanisms through which an organizational con-text that supports creativity impacts creative per-formance. Theoretically, contextual conditions arebelieved to influence creative performance via theireffects on employees’ intrinsic motivation (Shalleyet al., 2004). However, empirical research on themediating role of intrinsic motivation has yieldedinconsistent results (Shalley & Perry-Smith, 2001;Shin & Zhou, 2003). In response to these inconsis-tent results, Shalley and colleagues (2004) sug-gested that contextual characteristics may not onlyaffect creative performance via intrinsic motivationbut also via a number of alternative mechanisms.As Scott and Bruce (1994) suggested, supportivecontexts may also channel and direct employees’behaviors toward creative performance. We believefeedback-seeking behavior to be one such addi-tional behavioral mechanism.

Though organizational support for creativity hasnot been directly related to employees’ feedback-seeking behaviors, Ashford et al. (2003) alluded tothe possible role of a supportive organizationalcontext. They argued that in supportive organiza-tional contexts, employees experience few negativeconsequences when they directly ask for feedback.Research showing that supportive contexts neutral-ize employees’ image concerns about creative“voice” (Zhou & George, 2001), about raising issuesin organizations (Ashford, Rothbard, Piderit, & Dut-ton, 1998), and about engaging in innovative behav-ior (Yuan & Woodman, 2010). In view of this re-search, we propose that when there is perceivedsupport for creativity, employees see fewer risks inengaging in behaviors promoting their creative per-


formance, including seeking feedback abouttheir work.

A supportive context may also stimulate employ-ees to be more attentive to indirect feedback cuesabout their performance. Employees working incontexts supportive of their creativity experiencetheir organizations as accepting their input andideas and see management throughout those organ-izations as open and attuned to employees’ sugges-tions for improvement (Zhou & George, 2001). Em-ployees may respond to this organizationalattentiveness to feedback from them by being moreopen to feedback themselves and by monitoringtheir environment for feedback to bolster theirwork performance. Indeed, research in related ar-eas suggests that employees tend to reciprocate thepresence of perceived organizational support byengaging in continuous learning behaviors, for in-stance by participating in developmental experi-ences that are beneficial to their organization(Wayne, Shore, & Liden, 1997), seeking organiza-tion-relevant information, learning important workskills (Rhoades & Eisenberger, 2002), and engagingin self-reflection (West & Richter, 2008).

In addition to enhancing the frequency of feed-back seeking, a context that supports creativity mayalso stimulate employees to seek feedback from awider variety of sources. Researchers have pro-posed that in organizations in which creativity isencouraged, employees are stimulated to processinformation from diverse sources and to buildbroad networks (West & Richter, 2008). Such con-texts are also more likely to convey that manyindividuals, not only those within employees’ im-mediate work groups (e.g., their immediate super-visors and coworkers), but also individuals in otherdepartments and even outside the employees’ ownorganization (Cole, Schaninger, & Harris, 2002) areavailable and willing to help with developmentalneeds. Further, in the same way that supportivecontexts reduce barriers to more frequent feedbackseeking, they also reduce perceived obstacles toseeking feedback broadly (for instance, by reducingperceived image costs associated with asking forfeedback across departmental lines). As such, webelieve that contexts that support creativity alsoencourage employees to acquire feedback from abroader variety of feedback sources.

All these elements suggest the possible role of asupportive climate in the feedback-seeking process.Accordingly:

Hypothesis 4a. Perceived organizational sup-port for creativity is positively associated withemployees’ feedback-seeking behaviors: Themore employees perceive organizational sup-

port for creativity, the more frequently theyinquire for feedback.

Hypothesis 4b. Perceived organizational sup-port for creativity is positively associated withemployees’ feedback-seeking behaviors: Themore employees perceive organizational sup-port for creativity, the more frequently theymonitor for feedback.

Hypothesis 4c. Perceived organizational sup-port for creativity is positively associated withemployees’ feedback-seeking behaviors: Themore employees perceive organizational sup-port for creativity, the more broadly they in-quire for feedback.

Hypothesis 4d. Perceived organizational sup-port for creativity is positively associated withemployees’ feedback-seeking behaviors: Themore employees perceive organizational sup-port for creativity, the more broadly they mon-itor for feedback.

The Relationship between Traits and Contextand Creative Performance

We hypothesize that employees’ feedback-seek-ing behaviors mediate the relationship betweenour independent variables—individuals’ cognitivestyle and perceived organizational support for cre-ativity—and creative performance. That is, we pro-pose that people operating in supportive contextsand with an innovative style have higher levels ofcreative performance because they seek feedbackmore frequently and broadly. Their proactive self-regulation gives them more information and morediverse information from which to derive creativeideas. Because we assume that variables other thanfeedback seeking may explain the effects of thesevariables on creative performance (e.g., intrinsicmotivation), we expect the mediation to be partial.

Hypothesis 5a. The impact of cognitive stylesand perceived organizational support for cre-ativity on creative performance is partially me-diated by the frequency of employees’ inquiryand monitoring feedback-seeking behaviors.

Hypothesis 5b. The impact of cognitive stylesand perceived organizational support for cre-ativity on creative performance is partially me-diated by the breadth of employees’ inquiryand monitoring feedback-seeking behaviors.


METHODS

Data and Sample

Data were collected as part of a larger researchproject on proactivity and feedback dynamics inorganizations. The sample consisted of 456 super-visor-subordinate dyads from four consultingfirms, each employing between 300 and 800 em-ployees. We focused on the “knowledge workers”in these firms. Although creativity is not an explicitpart of knowledge work, creating new knowledgeand approaching their work creatively is thought tobe important to success in such work (Davenport,2005).

Two sets of online questionnaires were used: asurvey for subordinates and a survey for their im-mediate supervisors. For each organization, we de-veloped a database of knowledge workers in coop-eration with the human resources department,using Davenport’s definition of knowledge work asour selection criteria: “Knowledge workers havehigh degrees of expertise, education, or experience,and the primary purpose of their jobs involves thecreation, distribution or application of knowledge”(2005: 19). Because of the nested structure of ourdata (that is, subordinates are “nested within” theirsupervisors, and supervisors’ work groups arenested within their organizations), the database in-cluded information about employees’ work groupand team supervision.

Employees and their supervisors filled out theonline survey during regular working hours. Tolimit the burden on the supervisors, who each su-pervised 3 to 11 employees (the average was 4.3),we asked them to evaluate the creative performanceof just 3 of their subordinates, whose names wereselected at random. After 3 subordinates had beenevaluated, the supervisors had the option of evalu-ating their other subordinates as well. Each partic-ipating supervisor evaluated on average 3.73 em-ployees.1 From a population of 908 employees and162 managers, 661 employees and 122 supervisorsfilled out the survey (a response rate of 73 percentfor both groups), and we obtained 456 usable su-pervisor-subordinate dyads out of 908 possible dyads(an effective response rate of 50.2 percent). On aver-age, the employees in the sample had 2.79 years of jobtenure and had worked in their organization for 3.3

years. The average dyadic relationship length was2.63 years. Fifty-six percent of the sampled employ-ees were female; 76 percent worked full-time; andtheir average age was 34 years.

Measures

Cognitive style. We used a 13-item reduced ver-sion of the Kirton Adaptation-Innovation (KAI) In-ventory validated by Bagozzi and Foxall (1995)2 inthree different samples to measure cognitive style.Respondents were asked to indicate, on a scaleranging from 1 (“very hard”) to 5 (“very easy”), howdifficult it would be for them to maintain specifictypes of innovative and adaptive behaviors. A sam-ple item from the scale is “Create something newrather than improve it.” Kirton (1976) proposed asingle continuum of cognitive styles anchored by“innovative style” on one end and “adaptive style”on the other. In validation research, Bagozzi andFoxall (1995) concluded that this construct wasbetter represented by three dimensions: originality,efficiency, and rule governance. An innovativestyle would entail higher scores on originality andlower scores on efficiency and rule governance,and an adaptive style would correspond to lowerscores on originality and higher scores on effi-ciency and rule governance. Bagozzi and Foxall,however, also assessed whether a higher-order fac-tor might underlie these three dimensions andfound support for that conclusion.

We examined both of Bagozzi and Foxall’s (1995)conclusions in our data. In line with Baer, Oldham,and Cummings (2003), we found support for ahigher-order factor solution with one second-orderfactor (representing cognitive style) and three first-order factors (representing the three subdimensionsreported by Bagozzi and Foxall [1995]). This modeldemonstrated an acceptable fit and adequate mea-surement properties (� � .83; �2 � 59.04, df � 62, p� .05; NNFI � .99, CFI � .99, RMSEA � .00). Giventhese results, we used the three subdimensions asindicators of a latent “innovative style” variable. Thislatent second-order construct thus incorporates thethree first-order dimensions in such a way that higherscores represent an innovative cognitive style.

Perceived organizational support for creativ-ity. We measured perceived organizational supportfor creativity using three items from Zhou and

1 We tested for significant differences between the re-spondents who were rated by their superior and thosewho were not rated with regard to all study variables.Chi-square tests (i.e., for demographic variables) andtwo-sample t-tests indicated no significant differencesbetween the rated and the nonrated respondents.

2 Scales based on the KAI Inventory (Kirton, 1976,2003) were used with the express permission of Dr. Mi-chael Kirton. Since we could not use the complete ver-sion, Dr. Kirton suggested that this part of our studyshould be considered a pilot.


George’s (2001) scale, which was adapted from ascale developed by Scott and Bruce (1994; � � .85).A sample item is “Creativity is encouraged at[company].”

Frequency of feedback inquiry. Most feedbackseeking studies have assessed feedback seekingfrom supervisors (Chen et al., 2007; Lam, Huang, &Snape, 2007) or have not distinguished among var-ious feedback sources. One notable exception is ascale that Callister, Kramer, and Turban (1999)adapted from Ashford’s (1986) original feedbackseeking scales. The scale distinguishes between su-pervisor feedback inquiry and coworker feedbackinquiry. Because we sought to assess feedback seek-ing that extends beyond supervisors and immediatecoworkers, we further adapted the scale to capturea broader range of others that employees may con-sult when seeking feedback (Miller & Jablin, 1991;Morrison, 1993): supervisors, coworkers, other or-ganizational sources (e.g., peers in other depart-ments), and extraorganizational sources (e.g., peersin other organizations). Using a scale ranging from1 (“never”) to 5 (“very frequently”), respondentsindicated the extent to which the statements corre-sponded to their own behavior. Sample items include“How frequently do you directly ask your supervisorfor feedback about your work?” and “How frequentlydo you directly ask your supervisor for an informalappraisal of your work” (each question was repeatedfor each of the feedback sources).

The scales measuring feedback inquiry from col-leagues in other departments and from extraorgan-izational sources were developed for this research.We therefore first conducted an exploratory factoranalysis (EFA) on all the feedback seeking items onhalf of the sample, using principal componentsanalysis with a varimax rotation. Inspection of theeigenvalues and scree plots suggested that four fac-tors were represented in the data, corresponding tothe four sources of feedback seeking. In a next step,we conducted a confirmatory factor analysis (CFA)on the other half of the data and found an accept-able fit for a single second-order factor solutionwith the feedback sources as four distinct first-order factors (� � .84; �2 � 47.75, df � 50, p � .05;NNFI � .99, CFI � .99, RMSEA � .00). This singlesecond-order factor solution supports Morrison’s(1993) claim that individuals have a general ten-dency to seek feedback from various sources butthat they also differentiate among the sources.

Frequency of feedback monitoring. Items mea-suring feedback monitoring were adopted from thescales developed by Ashford and colleagues (Ash-ford, 1986; Ashford & Tsui, 1991). Eight itemsasked how frequently respondents observed andmonitored the behaviors of others to obtain infor-

mation about their own performance (� � .72).Sample items include “How frequently do you payattention to how your boss acts toward you in orderto understand how he/she perceives and evaluatesyour work?”; “How frequently do you compareyourself with peers in your organization (i.e., per-sons at your level within the organization?)”; and“How frequently do you compare yourself withpeers in other organizations (i.e., persons at yourlevel within other organizations)?” An EFA on halfof the sample and a CFA on the other half revealedthat one factor was represented in the data. Thus,respondents had an overall propensity to monitorfor feedback and did not differentiate among thevarious feedback sources. Given this finding, wewere unable to examine Hypothesis 2b, and weexamined our breadth hypotheses for inquiry only.

Breadth of feedback inquiry. To capture theextent to which individuals allocated their feed-back inquiry efforts among the four targets of seek-ing examined in this study, we turned to an indextypically used in economics to calculate a firm’smarket share across industries (Kelly, 1981), theHerfindahl index. In economics, this statistic givesan estimate of a firm’s emphasis on one industryversus its spread across several. In our case, it cap-tures the “market share” of a person’s feedbackseeking that is allocated to each target of that seek-ing. By summing these shares, we created a mea-sure of breadth. The calculation is:

Herfindahl index � �1 � ��seeking from supervisortotal seeking �2

� �seeking from team peerstotal seeking �2

� �seeking from peers in other departmentstotal seeking �2

� �seeking from external peerstotal seeking �2��. (1)

The result is an index that ranges from 0 to .75,with high scores representing greater breadth.

Creative performance. Following prior re-search, we used supervisor ratings to assess em-ployees’ creative performance (Zhou, 1998, 2003;Zhou & George, 2001). Using 13 items (Zhou, 1998),supervisors rated the creative performance of theirsubordinates on a scale ranging from 1 (“not at allcharacteristic”) to 5 (“very characteristic”). Asample item taken from the scale is “Comes upwith creative solutions to problems.” As in previ-ous research, these items loaded on a single factor(� � .84).


Controls. Prior research has shown that employ-ees’ tendency to seek feedback in part depends onthe length of their work experience (e.g., Ashford,1986; Ashford & Black, 1996). In keeping with otherfeedback seeking studies (e.g., VandeWalle, Gane-san, Challagalla, & Brown, 2002), we therefore ex-amined the role of job tenure. Following previouscreativity research (Zhou, 2003), we also examinedthe control variables of age and organizational po-sition. Finally, to assess the potential effects of theorganization in which an individual is employedand of the relationship between a sampled super-visor and subordinate, we examined the role ofcompany membership and the length of the dyadicrelationship between subordinate and supervisor(as reported by the subordinate).

Data Considerations and Analytical Plan

After inspecting the measurement properties ofour variables, we examined several aspects of ourdata. First, we ensured that the assumptions ofnormality, homogeneity of variance, linearity, andabsence of multicollinearity were met. Because thedata had a nested structure, we also checked for thepresence of dependence within the work groupsand for supervisor effects on ratings of creativeperformance (Kenny, Kashy, & Cook, 2006). To as-sess dependence in our data, we followed the pro-cedure recommended by Lam et al. (2007) and con-ducted two series of analyses. In the first series, wetested our model using multilevel modeling (HLM6.06) to control for the effects of different supervi-sors. To assess the extent to which group-level ef-fects were biasing our estimates, we analyzed ICC1,ICC2, and rwg(j) values, which here would respec-tively indicate the proportion of variance in ratingsdue to team membership (Bliese, 2000), the reliabil-ity of the team mean differences (Bliese, 2000), andwithin-group agreement for multiple item mea-sures (James, Demaree, & Wolf, 1984). ICC valuesand rwg(j) can range between 0 and 1, with higherscores indicating that group-level effects are pres-ent. There is no generally agreed upon cutoff valuefor ICC1 values (Kanfer, Chen, & Pritchard, 2008),but the typical cutoff for both rwg(j) and ICC2 is .70(Klein & Kozlowski, 2000). In our study, values forall three statistics were low, indicating that group-level effects were not biasing our results (perceivedorganizational support for creativity: ICC1 � .08,ICC2 � .25, rwg(j) � .17; cognitive style: ICC1 � .05,ICC2 � .16, rwg(j) � .15; feedback inquiry: ICC1 �.08, ICC2 � .25, rwg(j) � .17; feedback monitoring:ICC1 � .04, ICC2 � .13, rwg(j) � .20; for supervisor-rated creative performance: ICC1 � .09, ICC2 � .27,rwg(j) � .19).

Because our frequency and breadth measuresconsisted of different treatments of the same data,we did not test a single model of all of our hypoth-eses. Rather, we tested the frequency and breadthhypotheses separately, using regression analysis totest our breadth hypotheses and structural equationmodeling (SEM) to test our frequency hypotheses.As these analyses yielded results similar to those ofthe HLM analyses and given the low ICC and rwg(j)

values, we followed the recommended approach ofonly reporting the results of the regression and pathanalyses (Lam et al., 2007; van der Vegt, van deVliert, & Oosterhof, 2003).3, 4

RESULTS

Table 1 presents the means, standard deviations,reliability coefficients, and correlations among thestudy variables.

Analyses Regarding Frequency of Seeking

The indicators and constructs were formed asfollows: For constructs with a higher-order factorstructure (e.g., inquiry and cognitive style), we re-duced the number of parameters to be estimatedfollowing the partial aggregation method (Bagozzi& Edwards, 1998; Little, Cunningham, & Shahar,2002). This procedure involves averaging re-sponses on subsets of items measuring a construct.On the basis of exploratory and confirmatory factoranalyses, we formed three indicators for cognitivestyle (representing the three subscales) and fourindicators for employees’ feedback-seeking inquiry(representing the four sources). Because monitoringand creative performance were unidimensional con-structs, we followed the procedure recommended by

3 Controls were included in the HLM analyses. Wetested the model both with and without control variables.Because the results of both analyses were the same, thecontrol variables were not included in the SEM analysis.However, to hold control variables constant for the SEManalysis without using up degrees of freedom, we fol-lowed a procedure used by Kammeyer-Mueller and Wan-berg (2003) in which control variables were partialed outof the covariance matrix prior to analysis.

4 In line with previous research (Tierney et al., 1999),we also tested whether employee cognitive style andperceived organizational support for creativity interactedin impacting creative performance. The regression anal-ysis showed no impact of the interaction of cognitivestyle and perceived organizational support for creativityon creative performance (� � –.01, n.s.), nor did the inter-action relate to the feedback-seeking behaviors (� � –.05,n.s., for inquiry; � � –.02, n.s., for monitoring).


Little et al. (2002) and created three parcels of ran-domly selected items to serve as indicators for thesevariables. Perceived organizational support for cre-ativity was measured with only three items, so, inkeeping with the total disaggregation model (Bagozzi& Edwards, 1998), we used the item scores as theindicators for these constructs.

To test our conceptual model, we followed theprocedure described by Bagozzi and Bergami (2000).

Specifically, we compared a fully mediated base-line model to a number of alternatives, includingthe hypothesized model specifying partial media-tion. The chi-square test for this baseline modelwas significant and thus indicated poor fit (�2 �135.40, df � 96, p � .05), a result frequently foundwith large samples. The other fit indexes, however,indicated that our model fitted our data well(NNFI � .98, CFI � .99, RMSEA � .03).

TABLE 2Comparison of the Baseline Structural Model to Alternative Models

Model �2 df ��2 Conclusion

Baseline: Fully mediated 135.40 96

Alternative 1: Hypothesizeda Significantly better fit than baseline model.Perceived organizational support for creativity 3

creative performance relaxed101.32 94 34.08** Both paths were significant.

Cognitive style 3 creative performance relaxed

Alternative 2: 101.82 95 0.50 Most parsimonious model.Alternative 1 with monitoring 3 creative

performance fixed to 0

Alternative 3: 141.40 97 40.08** Significantly poorer fit than alternative model 2.Alternative 2 withPerceived organizational support for creativity 3

monitoring fixed to 0Cognitive style 3 monitoring fixed to 0

a Figure 1 shows the hypothesized model.**p � .01

TABLE 1Means, Standard Deviations, Reliabilities, and Correlationsa

Variable Mean s.d. 1 2 3 4 5 6 7 8 9 10 11 12 13

1. Cognitive style 3.82 0.61 (.83)2. Perceived organizational

support for creativity3.44 0.75 .15** (.85)

3. Frequency of inquiry 2.71 0.62 .21** .20** (.84)4. Inquiry from supervisor 2.81 0.68 .12** .15** .62** (.83)5. Inquiry from department

peers2.78 0.63 .09* .12** .68** .26** (.89)

6. Inquiry fromorganizational peers

2.54 0.60 .15** .09 .68** .21** .31** (.81)

7. Inquiry from peers inother organizations

2.38 0.61 .21** .17** .71** .21** .32** .37** (.81)

8. Monitoring 3.50 0.64 .12** .20** .35** .30** .21** .05 .11* (.70)9. Breadth of inquiry

(Herfindahl index)0.71 0.03 .11** .16** .30** .10* .10* .19** .20** .21**

10. Creative performance 3.03 0.84 .23** .16** .23** .17** .18** .10* .18** .10* (.84)11. Organization tenure 3.3 4.21 .09 .08 �.05 .03 �.02 .01 .02 .04 .0312. Age 34 14.8 �.08 .07 �.03 .02 .04 .03 .05 .07 �.06 .10*13. Position 0.22 0.36 �.05 .06 �.02 .01 .04 .05 .05 .10* �.03 .04 .10*14. Company 2.1 0.70 .02 .09 �.09 �.08 �.05 �.06 �.06 .03 �.03 .02 .03 .0415. Dyad length 2.63 4.51 .09 .08 �.05 .03 �.01 .01 .03 .06 .04 .10* .09 .09 .02

a Values on the diagonal in parentheses represent the coefficient alpha reliabilities.* p � .05

** p � .01


In a next step, we compared this baseline modelwith a number of alternative models to determinewhether our model was sufficiently parsimoniousand comprehensive. Table 2 reports the resultsfrom these analyses. First, we compared the base-line with our hypothesized, partially mediatedmodel, which is shown in Figure 1. Thus, we addedtwo additional direct paths to the baseline model:one from cognitive style to creative performanceand one from perceived organizational support forcreativity to creative performance. This saturatedmodel fitted our data significantly better (�2 �101.32, df � 94, p � .05; NNFI � .99, CFI � .99,RMSEA � .01; ��2[2] � 34.08, p � .01). Figure 1reports the parameter estimates for this structuralmodel. As the figure shows, the structural equationanalysis shows that employees’ feedback inquiry(but not their feedback monitoring) is significantlyrelated to creative performance, supporting Hy-pothesis 1a (path coefficient � .32, p � .05), but notHypothesis 1b (path coefficient �.06, n.s.). Cogni-tive style and perceived organizational support forcreativity impact the frequency of feedback inquiry(path coefficient � .35, p � .05, for cognitive style;path coefficient � .21, p � .05, for perceived organ-izational support for creativity) and feedback mon-itoring (path coefficient � .17, p � .05, for cognitivestyle; path coefficient � .27, p � .05, for perceivedorganizational support for creativity), supportingHypotheses 3a, 3b, 4a, and 4b.The coefficients forthe paths from both cognitive style and perceivedorganizational support for creativity to creative per-formance were significant (.20, p � .05, and .22,p � .05, respectively), providing initial support forHypotheses 5a and 5b.

To further assess whether feedback inquiry (par-tially) mediates the relationship between our inde-pendent variables and creative performance, wealso followed the procedure recommended byJames, Mulaik, and Brett (2006). We first estimatedthe indirect effects and then used a bootstrappingtechnique to construct confidence intervals (Stine,1989). The indirect effects were both significant(.04 for the path from perceived organizational sup-port for creativity to supervisor-rated creative per-formance via feedback inquiry and .08 for an inno-vative cognitive style to supervisor rated creativeperformance via feedback inquiry), suggesting thatfrequent feedback inquiry serves as a partial medi-ator between our antecedents and supervisor-ratedcreative performance. Thus, the structural equationanalyses show that the frequency of feedback in-quiry mediates the impact of cognitive style andperceived organizational support for creativity oncreative performance, but suggests partial media-tion, thereby supporting Hypothesis 5a.

Given that we found a nonsignificant path frommonitoring to creative performance in both thebaseline and the hypothesized models, we alsocompared these models to one in which we fixedthe path coefficient from monitoring to creativeperformance to zero (i.e., alternative model 2 inTable 2). This model did not significantly changeour chi-square statistic, bolstering our previousfinding that Hypothesis 1b was not consistent withour data (�2 � 101.82, df � 95, p � .05; NNFI � .99,CFI � .99, RMSEA � .01; ��2[1] � .50, n.s.).

Next, to assess whether an even more parsimoni-ous model would fit our data equally well, we alsodropped the paths from the independent variablesto monitoring. This deletion significantly worsenedthe fit of alternative model 2 (�2 � 141.40, df � 97,n.s.; NNFI � .98, CFI � .98, RMSEA � .03; ��2[2] �40.08, p � .05), indicating that this model was notsufficiently comprehensive. In summary, the resultsof our structural equation analysis show that bothcognitive style and perceived organizational supportfor creativity affect employees’ creative performanceand that how frequently employees inquire for feed-back partially mediates these effects.

Analyses Regarding Breadth of Feedback Seeking

Results regarding the Herfindahl statistic suggestthat our sample members tended to spread theirfeedback inquiry across targets (the mean for theentire sample was .71). A regression of supervisor-rated creative performance on the Herfindahl indexfor feedback inquiry showed a significant impact ofthe breadth of inquiry on supervisor-rated creativeperformance (� � .22, p � .01). This result supportsHypothesis 2a and suggests that individuals benefitfrom seeking more broadly from various sources offeedback.

To test whether breadth of seeking mediates therelationship between innovative style, perceivedorganizational support for creativity and supervisorratings of creative performance, we followed pro-cedures established by Baron and Kenny (1986).We first regressed supervisor-rated creative perfor-mance on our independent variables. We found apositive effect of perceived organizational supportfor creativity (� � .13, p � .01) and of an innovativecognitive style (� � .21, p � .01) on supervisor-rated creative performance. When we subsequentlyentered the independent variables and the Herfin-dahl statistic (capturing breadth) simultaneouslyinto the regression, we found a significant impactof breadth of inquiry on supervisor-rated creativeperformance (� � .22, p � .01). However, perceivedorganizational support for creativity and an inno-vative cognitive style remained significant predic-


tors of supervisor-rated creative performance (� �.09, p � .05, for perceived organizational supportfor creativity, and � � .192, p � .01, for an inno-vative style), thereby excluding full mediation(Baron & Kenny, 1986). Given that the mediationtest we performed is a conservative one for assess-ing meditational effects (MacKinnon, Lockwood,Hoffman, West, & Sheets, 2002), we also testedwhether the indirect paths from our independentvariables (via breadth of seeking) to supervisor-rated creative performance were significant usingthe Preacher-Hayes (2008) bootstrapping proce-dure. In support of Hypothesis 5c, these testsshowed that the indirect paths from perceivedorganizational support for creativity (via breadth)and from an innovative style (via breadth) weresignificant (indirect path � .03, p � .05, for per-ceived organizational support for creativity, and.02, p � .05, for innovative style). These analysesprovide support for an indirect impact of ourindependent variables on supervisor-rated cre-ative performance via the breadth of feedbackseeking (Hypothesis 5b).

As stated, for monitoring, respondents did notdifferentiate among the various feedback sources.Given this finding, we did not test our breadthhypothesis for monitoring, thereby disconfirmingHypotheses 2b and 5d.

In sum, the results of our regressions and SEManalyses show that an innovative cognitive styleand perceived organizational support for creativityenhance creative performance and that the fre-quency and breadth of individuals’ feedback in-quiry partially mediate this relationship. Monitor-ing for feedback was also positively associated withour independent variables but did not predictcreative performance at a statistically significantlevel.

DISCUSSION

This study highlights a new avenue for enhanc-ing employees’ creative performance. In addition toselecting employees with sensitivity to their inno-vative cognitive styles (Foxall, 1990) and buildingcontexts that support an appropriate style of cre-ativity, managers can also work to promote individ-uals’ independent self-regulation and self-enhance-ment of their own work to promote creativeperformance. Our results suggest that proactiveself-regulatory behaviors, at least in the form offeedback seeking about job performance via in-quiry, play a role in achieving creative outcomes.They partially mediate effects of cognitive style andperceived organizational support for creativity oncreative performance.

Our findings extend previous research in at leastthree ways. First, the results of this study directlysupport recent arguments for greater attention toemployee proactivity and self-starting behavior atwork (Grant & Ashford, 2008). Traditionally, thecreativity literature has focused on how managerscan foster and stimulate creative performance by,for example, setting explicit goals for creativity andproviding developmental feedback to employees.These suggestions implicitly portray employees asrelatively reactive agents in the creative process whoneed to be motivated and led by others. This viewfails to recognize the self-regulating potential of em-ployees. Rather than portraying creativity as organi-zationally driven, the results of this study show thatemployees can actively stimulate their creative per-formance by soliciting feedback on their work andperformance frequently and from a wide variety ofsources. This finding supports our theoretical posi-tion that diversifying input and information aboutone’s work produces more creative performance.

Second, our study adds to the creativity literatureby testing a model that examines how disposi-tional, contextual, and behavioral factors simulta-neously contribute to creative performance. Takinga process focus on creative performance, we foundthat feedback-seeking behavior is a relevant inter-vening variable in the relationships among em-ployee cognitive style, perceived organizationalsupport for creativity, and creative performance.Whereas prior work has demonstrated the directimpact of these factors on creative performance(Baer et al., 2003; Oldham & Cummings, 1996; Tier-ney & Farmer, 2002), our study is one of the first toidentify a behavioral mechanism through whichthese factors impact it. It is possible that feedbackseeking is one of a more general set of creativity-relevant skills and strategies that increase creativeperformance. This possibility suggests that in addi-tion to selecting employees with creative personal-ities and building a context that supports creativity,organizations and individuals can also build self-regulation skills to enhance the creative process,and organizations can encourage employees to seekfeedback on their performance more often andmore broadly. In addition to feedback seeking, fu-ture research might explore strategies such as self-set goals (Lee, Locke, & Latham, 1989), mindfulness(Langer, 1989), motivation maintenance (Grant,Campbell, Chen, Cottone, Lapedis, & Lee, 2007),and self-reward and punishment (Kanfer & Karoly,1972). This examination of individual behaviorssupplements a robust literature on person and con-text predictors of creative performance.

Finally, our results highlight a different concep-tualization of the role of feedback and feedback


seeking in producing outcomes. Feedback seekinghas traditionally been depicted as a strategy thathelps individuals to conform to the requirements oftheir environment in a process of individual adjust-ment (Ashford et al., 2003; Ashford & Taylor, 1990;Parker & Collins, 2010). By relating creativity-rele-vant individual traits and context factors to feed-back-seeking behavior and by linking individuals’overall propensity to inquire for feedback from var-ious sources to creative performance, our studyresults highlight that feedback seeking is an indi-vidual resource that can help individuals toachieve a variety of outcomes, including creativeresponses that may deviate from (rather than adaptto) their environment in positive ways. Such anextension of the scope of feedback seeking researchis suggestive of potential new research emphases inthe feedback seeking literature based on recent re-search in positive psychology. As Ashford et al.(2003) noted, this perspective motivates a shift fromfitting in to excelling and achieving distinction inorganizations—from adaptation to a setting to in-dividual agency, growth, and creation within it.

Our failure to find a statistically significant rela-tionship between feedback monitoring and creativeperformance was surprising. This finding may be afunction of the rather general items used in themonitoring scale. Alternatively, it may reflect themore ambiguous nature of the feedback obtainedvia monitoring. As a feedback-seeking strategy,monitoring may yield messages that are at bestsubtle, fleeting, ambiguous, and open to interpreta-tion. Thus, performers who are monitoring for feed-back may miss many cues representing others’views of their performance. Failing to pick up onthese cues results in the performers missing out onthe divergent viewpoints that we and others (Cohen& Levinthal, 1990; Perry-Smith, 2006) propose as avaluable stimulus to creative performance. An al-ternative explanation that might be explored in fu-ture research is that monitoring may actually createmore conformity and less creativity than inquiry.Inquiry involves an explicit, volitional act. Assuch, it may be undertaken more frequently byindividuals who are generally proactive, goal di-rected, and interested in regulating their own per-formance (Grant & Ashford, 2008). Monitoring, onthe other hand, may involve a more generalizedtendency to notice others’ opinions and to conformto them—a tendency about which a performer maynot even be fully conscious (Ashford et al., 2003).Our pattern of findings is somewhat consistentwith this possibility. The coefficient for innovativecognitive style and monitoring was .27, but that forinnovative cognitive style and inquiry was muchstronger (.46). It may be that inquiry gives more

explicit, but still personal, data from which a feed-back seeker might work to craft a creative response.Frequent monitoring might reflect more of an un-conscious tendency to play it safe and be vigilantabout others’ views in order to conform. This ideais speculation based on our pattern of findings.Future study is needed. Although the feedbackseeking literature to date has shown little empiricalevidence of differential predictors of inquiry versusmonitoring (Ashford et al., 2003), it may be thatthese strategies have different effects, with feed-back obtained by inquiry stimulating creativity andfeedback obtained by monitoring not doing so.

Practical Implications

Our study echoes recent suggestions that organi-zations interested in enhancing employees’ cre-ative performance might profitably focus on devel-oping work contexts that support it. As Shalley(2008) discussed, such contexts may be developedby setting creativity goals, making creativity a jobrequirement, providing feedback, and building re-ward systems that value employee creativity. Ourstudy suggests that supportive contexts should alsostimulate employees to inquire for feedback abouttheir work more frequently. To stimulate feedback-seeking behavior and enhance employees’ creativeperformance, organizations need to take steps toreduce or eliminate some of the documented imageconcerns associated with inquiring for feedback(Ashford, 1986), perhaps by developing a general“feedback climate” (Steelman, Levy, & Snell, 2004)that supports the spontaneous exchange of infor-mal feedback throughout an organization. This sug-gestion is consistent with Yuan and Woodman’s(2010) empirical findings in the innovation areashowing that context factors that reduced imagerisk promoted innovation.

Our results also suggest that if creative perfor-mance is an organization’s goal, there is value instimulating employees to seek feedback beyond thetraditional source, their supervisor, and to considerpeers and even extraorganizational sources. Organi-zations may develop contexts that support creativityby encouraging their employees to broaden their de-velopmental networks and seek feedback from mul-tiple sources, rather than limit themselves to super-visor-delivered feedback. Stimulating employees toparticipate in learning communities that span organ-izational boundaries may particularly facilitate theexchange of valuable feedback from outside, and thuscreativity (Nonaka, 1994; Raelin, 1997).

From an individual perspective, our results high-light that individuals interested in achieving cre-ative outcomes in their work may do so by seeking


feedback more frequently and from a wide varietyof feedback sources. For individuals, such seekingmay have a dual benefit: it not only helps them torefine their ideas and to obtain relevant new input,but may also be a way of promoting these ideas andmaking them visible to others (Ashford et al., 2003;Morrison & Bies, 1991).

Limitations

These results need to be considered in light ofseveral study limitations. First, all data were col-lected cross-sectionally with a survey methodol-ogy, so common method biases may have con-founded our results and may limit the confidencewith which we can draw conclusions about causal-ity (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003).However, as we collected measures of our predictorand outcome variables from different sources, theeffects of consistency motifs, implicit theories, andsocial desirability bias are somewhat reduced (Pod-sakoff et al., 2003). Our methodology also leavesopen the possibility that the effects found werespurious. To reduce the likelihood of this issue, wefollowed the advice of Rogelberg (2002) and basedour model on explicit theory in the feedback seek-ing and creativity literatures. Second, we also in-corporated a number of control variables to reducethe likelihood of spurious effects. Despite thesesteps, however, the possibility of spurious effectscannot be completely ruled out. Models tested overtime are needed.

Second, in testing Hypotheses 1a, 1b, 2a, and 2b,which were derived from Kirton’s (1994) adaption-innovation theory, we were not able to use the KAIinventory fully. Future research using the full KAIinstrument is needed to confirm and extend theresults found in the present study. However, scalevalidation work undertaken by Bagozzi and Foxall(1995) did provide evidence of the construct valid-ity of the 15-item scale we used.

Third, reflecting our research question, our mea-sures asked generally about feedback-seeking be-haviors regarding performance using measures es-tablished in previous research. The measure formonitoring may have been too general. Althoughwe suggested some possible theoretical explana-tions, the generality of these items also may ac-count for the lack of findings tying monitoring tocreative performance. Future research using a dif-ferent measure might assess this possibility. Ourmeasures did, however, make one possible con-found less likely in our research. That is, becausewe measured feedback seeking about job perfor-mance generally, we reduced the likelihood of im-pression management as an alternative explanation

for our results. If individuals explicitly ask theirbosses, for example, “ How creative do you think Iam?” they may be truly interested, or they may beattempting to influence or manage their boss’ impres-sions of them as creative people. Our measure makesthis alternative explanation for results less likely.

Finally, this study used a sample from a singleindustry and a single type of job, consulting, forwhich creative performance wasn’t an explicit jobdemand (as it would be in a job explicitly requiringcreating something new, such as a web design or awriting). This sample was the perfect one in whichto test our ideas about whether seeking feedback onjob performance generally prompted greater creativ-ity. For jobs in which creative performance is anexplicit job requirement, researchers could measureindividuals’ explicit attempts to seek feedback abouttheir creativity. Future research might test whetherour findings generalize to different types of knowl-edge or creative workers in different industries.

Avenues for Future Research

This research suggests several possibilities forfuture or empirical study. First, we introducedfeedback-seeking behavior as a possible additionalmechanism explaining the effects of individual dif-ferences and context factors on creative perfor-mance. Although its role as a mediator of theseeffects was established only for the frequency ofinquiry, both feedback-seeking frequency andbreadth were related to creative performance.These findings suggest that researchers should con-tinue study of both the behaviors and attributes ofemployees, such as their intrinsic motivation orpersonality factors, as causes of their creative per-formance. For guidance regarding additional be-haviors to examine, one might draw on work byVandeWalle and colleagues (1999), who found thatgoal setting, effort, and planning were importantself-regulation tactics for sales performance, or onwork by Porath and Bateman (2006), who identifiedproactive behavior, emotional control, and socialcompetence as key self-regulatory skills for em-ployees. The role of these behaviors in enhancingcreative performance is as yet unexplored. Also,even though this study contributes to a literaturethat is establishing additional mediators for theeffects of person and context variables on creativeperformance (e.g., Gong et al., 2009), this literaturehas not yet assessed the unique explanatory powerrelative to previous explanations including intrin-sic motivation. Future research should examinemodels comparing various mediators by combiningbehaviors individuals undertake to enhance theircreative performance with individual factors such


as intrinsic motivation and other contextual factorsto assess the role of behaviors relative to traits andcontext variables more generally.

Second, research that broadens our examinationof feedback information and feedback seeking intwo ways would be valuable. First, it’s important toexplore how the seeking of various types of infor-mation affects the creative process. Employees seeknot only information about how they are perform-ing, but other types of information as well, such astask information about the technical aspects oftheir jobs, information about their roles in theirorganizations, social information about how to be-have, and organizational information about proce-dures and policies (Morrison & Vancouver, 2000).Future research should explore whether and howthese types of information seeking may be of valueto employees’ creative performance. Second, itwould be valuable to theorize about and assess themediating processes by which information andfeedback seeking enhance creative performance.For example, getting more information and/or feed-back may give performers ideas that they didn’thave previously or more confidence about raisingtheir ideas in the workplace and incorporatingthem into their performance. Given the perceptualmeasure of creative performance used in this andmost research on creative performance, variables in-fluencing not only people’s ideas, but also their will-ingness to speak up about them, become important.

Third, future research should also assess howindividuals’ propensity to inquire for feedbackbroadly from different sources affects outcome vari-ables other than creative performance. It may bethat employees’ general tendency to seek feedbackbroadly from various sources and the impact ofsuch breadth differ depending on the outcome un-der investigation. For example, when employeesuse feedback seeking as a strategy to mold them-selves to the prevailing view of what constitutesacceptable or successful behavior in their immedi-ate work context, they may be better off limitingthemselves to seeking feedback from sources whoendorse prevalent standards (e.g., their supervisor).Seeking feedback from a wider variety of sources(e.g., peers in other organizations) may even havedisruptive effects, because these sources might pro-vide the seeker with ideas that are considered de-viant and inappropriate in their own work context.Thus, although our results highlight that individu-als may achieve higher levels of creative perfor-mance with broad seeking, its effects may take on adifferent pattern depending on the outcome underinvestigation.

Finally, if we move away from studying creativeperformance (a general tendency to introduce cre-

ative ideas in one’s job) toward the study of jobsthat are explicitly about creation, then issues of thetiming of various individual actions related to cre-ative performance become important. For example,at some stages in the creative process feedback maydestroy or diminish creativity, and feedback seek-ing should not be undertaken. Specifically, feed-back seeking may be crucial in an idea generationphase to help employees refine their ideas, but itmay become detrimental in the idea promotionphase (when employees sell their ideas to internalor external sponsors). As De Stobbeleir and Declip-peleer (2010) suggested, in this later stage, employ-ees need to be persistent in sticking to their ideas toget the ideas sold. Feedback monitoring and in-quiry may also play differing roles at differentstages in the creative process. When an idea is stillpremature, employees may monitor their environ-ment for indirect feedback cues to obtain an initialassessment of the viability of the idea. On the basisof this initial indirect feedback, they can then de-cide whether or not to pursue and refine the idea.When employees decide to further develop an idea,they may then decide to directly ask others for theirfeedback. Hence, rather than contributing directlyto creative performance, monitoring may help in-dividuals to channel their energy toward ideas thatare worth pursuing. Testing this process view of therole of feedback at different stages in the creativeprocess with longitudinal research designs and sam-ples in which the creation of new ideas, products,and approaches is the explicit focus of jobs couldhelp develop a more complete picture of the process.

Conclusions

Our study breaks new ground in the creativity lit-erature by highlighting individuals’ proactive role inenhancing their creative performance. The results in-dicate that individuals can enhance their own cre-ative performance by actively seeking feedback ontheir work from various sources. Our findings high-light the importance of studying employees’ self-reg-ulatory behaviors in the creative process and supportthe proposition that feedback seeking is not only astrategy that facilitates individual adaptation, but alsoan individual resource that can help individuals toachieve creative outcomes.

REFERENCES

Amabile, T. M., & Mueller, J. S. 2008. Studying creativity,its processes, and its antecedents: An exploration ofthe componential theory of creativity. In J. Zhou &C. E. Shalley (Eds.), Handbook of organizationalcreativity: 33–64. New York: Erlbaum.


Ashford, S. J. 1986. Feedback seeking in individual ad-aptation: A resource perspective. Academy of Man-agement Journal, 29: 465–487.

Ashford, S. J., & Tsui, A. S. 1991. Self-regulation for man-agerial effectiveness: The role of active feedback seek-ing. Academy of Management Journal, 34: 251–280.

Ashford, S. J., & Black, S. J. 1996. Proactivity duringorganizational entry: The role of desire for control.Journal of Applied Psychology, 81: 199–214.

Ashford, S. J., & Cummings, L. L. 1983. Feedback as anindividual resource: Personal strategies of creatinginformation. Organizational Behavior and HumanPerformance, 32: 370–398.

Ashford, S. J., Blatt, R., & VandeWalle, D. 2003. Reflec-tions on the looking glass: A review of research onfeedback seeking behavior in organizations. Journalof Management, 29: 773–799.

Ashford, S. J., George, E., & Blatt, R. 2008. Old Assump-tions, new work: The opportunities and challengesof research on nonstandard employment. In J. P.Walsh & A. P. Brief (Eds.), Academy of Manage-ment annals, vol. 1: 65–117. New York: Erlbaum.

Ashford S. J., Rothbard, N., Piderit, S., & Dutton, J. 1998.Out on a limb: The role of context and impressionmanagement in selling gender-equity issues. Admin-istrative Science Quarterly, 43: 23–57.

Ashford, S. J., & Taylor, M. S. 1990. Adaptation to worktransitions: An integrative approach. In G. R. Ferris &K. M. Rowland (Eds.), Research in personnel andhuman resource management, vol. 8: 1–41. Green-wich, CT: JAI.

Baer, M., Oldham, G. R., & Cummings, A. 2003. Reward-ing creativity: When does it really matter? Leader-ship Quarterly, 14: 569–586.

Bagozzi, R. P., & Bergami, M. 2000. Self-categorization,affective commitment and group self-esteem as dis-tinct aspects of social identity in the organization.British Journal of Social Psychology, 39: 555–561.

Bagozzi, R. P., & Foxall, G. R. 1995. Construct validityand generalizability of the Kirton Adaption-Innova-tion Inventory. European Journal of Personality, 9:185–206.

Bagozzi, R. P., & Edwards, J. R. 1998. A general approach forrepresenting constructs in organizational research. Or-ganizational Research Methods, 1: 45–87.

Baron, R. M., & Kenny, D. A. 1986. The mediator-moder-ator distinction in social psychological research:Conceptual, strategic, and statistical considerations.Journal of Personality and Social Psychology, 51:1173–1182.

Bliese, P. 2000. Within-group agreement, non-indepen-dence, and reliability. In K. Klein & S. Kozlowski(Eds.), Multi-level theory, research, and methods inorganizations: 349–381. San Francisco: Jossey-Bass.

Callister, R. R., Kramer, M. W., & Turban, D. B. 1999.

Feedback seeking following career transitions.Academy of Management Journal, 42: 429–438.

Carver, C. S., & Scheier, M. F. 1981. Attention and self-regulation: A control-theory approach to humanbehavior. New York: Springer.

Chen, Z., Lam, W., & Zhong, J. A. 2007. Leader–memberexchange and member performance: A new look atindividual-level negative feedback-seeking behaviorand team-level empowerment climate. Journal ofApplied Psychology, 92: 202–212.

Cohen, W. M., & Levinthal, D. A. 1990. Absorptive-capacity—A new perspective on learning and innovation. Ad-ministrative Science Quarterly, 35: 128–152.

Cole, M. S., Schaninger, B., & Harris, S. G. 2002. Theworkplace social exchange network: A multilevel,conceptual examination. Group and OrganizationManagement, 27: 142–167.

Cools, E., & Van den Broeck, H. 2007. Development andvalidation of the Cognitive Style Indicator. Journalof Psychology, 141: 359–387.

Davenport, T. H. 2005. Thinking for a living: How to getbetter performances and results from knowledgeworkers. Cambridge, MA: Harvard Business School.

De Stobbeleir, K. E. M., & Declippeleer, I. 2010. Fromcreativity to success: Barriers and critical successfactors in the successful implementation of cre-ative ideas. Working paper, Vlerick Leuven GentManagement School.

De Vet, A. J., & de Dreu, C. K. W. 2007. The influence ofarticulation, self-monitoring ability, and sensitivityto others on creativity. European Journal of SocialPsychology, 37: 747–760.

Drazin, R., Glynn, M., & Kazanjian, R. K. 1999. Multileveltheorizing about creativity in organizations: A sen-semaking perspective. Academy of ManagementReview, 24: 286–307.

Drazin, R., Kazanjian, R. K., & Glynn, M. 2008. Creativityand sensemaking among professionals. In J. Zhou &C. E. Shalley (Eds.), Handbook of organizationalcreativity: Ch. 11. Hillsdale, NJ: Erlbaum.

Foxall, G. R. 1990. An empirical analysis of mid-careermanagers’ adaptive-innovative cognitive styles andtask orientations in three countries. PsychologicalReports, 66: 1115–1124.

Gangestad, S. W., & Snyder, M. 2000. Self-monitoring:Appraisal and reappraisal. Psychological Bulletin,126: 530–555.

Gong, Y., Huang, J., & Farh, J. 2009. Employee learningorientation, transformational leadership, and em-ployee creativity: The mediating role of employeecreative self-efficacy. Academy of ManagementJournal, 52: 765–778.

Grant, A. M., & Ashford, S. J. 2008. The dynamics ofproactivity at work. In A. P. Brief & B. M. Staw (Eds.),Research in organizational behavior, vol. 28: 3–34.Greenwich, CT: JAI.


Grant, A. M., Campbell, E. M., Chen, G., Cottone, K.,Lapedis, D., & Lee, K., 2007. Impact and the art ofmotivation maintenance: The effects of contact withbeneficiaries on persistence behavior. Organiza-tional Behavior and Human Decision Processes,103: 53–67.

Gryskiewicz, N. D., & Tullar, W. L. 1995. The relation-ship between personality type and creativity styleamong managers. Journal of Psychological Type,32: 30–35.

Higgins, M. C., & Kram, K. E. 2001. Reconceptualizing men-toring at work: A developmental network perspective.Academy of Management Review, 26: 264.

Hodgkinson, G. P., & Sadler-Smith, E. 2003. Complex orunitary? A critique and empirical re-assessment ofthe Allinson-Hayes Cognitive Style Index. Journal ofOccupational & Organizational Psychology, 76:243–268.

Houtz, J. C., Selby, E., Esquivel, G. B., Okoye, R. A.,Peters, K. M., & Treffinger, D. J. 2003. Creativitystyles and personal type. Creativity Research Jour-nal, 15: 321–330.

Isaksen, S. G., Lauer, K. J., & Wilson, G. V. 2003. Anexamination of the relationship between personalitytype and cognitive style. Creativity Research Jour-nal, 15: 343–354.

Jacobson, C. M. 1993. Cognitive styles of creativity: Re-lations of scores on the Kirton Adaption-InnovationInventory and the Myers-Briggs Type Indicatoramong managers in the USA. Psychological Reports,72: 1131–1138.

James, L. R., Demaree, R. G., & Wolf, G. 1984. Estimatingwithin-group interrater reliability with and withoutresponse bias. Journal of Applied Psychology, 69:85–98.

James, L. R., Mulaik, S. A., & Brett, J. M. 2006. A tale oftwo methods. Organizational Research Methods, 9:233–244.

Kammeyer-Mueller, J. D., & Wanberg, C. R. 2003. Unwrap-ping the organizational entry process: Disentanglingmultiple antecedents and their pathways to adjust-ment. Journal of Applied Psychology, 5: 779–794.

Kanfer, R., Chen, G., & Pritchard, R. (Eds.). 2008. Workmotivation: Past, present, and future. New York:Psychology Press.

Kanfer, F. H., & Karoly, P. 1972. Self-control: A behav-ioristic excursion into the lion’s den. BehaviorTherapy, 3: 398–416.

Kelly, W. 1981. A generalized interpretation of the Herfin-dahl index. Southern Economic Journal, 48: 50–57.

Kenny, D. A., Kashy, D. A., & Cook, W. L. 2006. Dyadicdata analysis. New York/London: Guilford.

Kirton, M. J. 1976. Adaptors and innovators: A descrip-tion and measure. Journal of Applied Psychology,61: 622–629.

Kirton, M. J. 1994. Adaptors and innovators (2nd ed.).London: Routledge.

Kirton, M. J. 2003. Adaption-innovation in the contextof diversity and change. London & New York:Routledge.

Kirton, M. J., & de Ciantis, S. M. 1986. Cognitive style andpersonality: The Kirton adaption-innovation andCattell’s sixteen personality factor inventories. Per-sonality and Individual Differences, 7: 141–146.

Klein, K. K., & Kozlowski, S. W. J. 2000. Multileveltheory, research and methods in organizations.San Francisco: Jossey-Bass.

Lam, W., Huang, X., & Snape, E. 2007. Feedback seekingbehavior and leader-member exchange: Do supervi-sor attributions matter? Academy of ManagementJournal, 50: 348–363.

Langer, E. 1989. Mindfulness. Cambridge, MA: Perseus.

Larson, J. J. 1989. The dynamic interplay between em-ployees’ feedback-seeking strategies and supervi-sors’ delivery of performance feedback. Academy ofManagement Review, 14: 408–423.

Lee, T. W., Locke, E. A., & Latham, G. P. 1989. Goalsetting theory and job performance. In L. Pervin(Ed.), Goal concepts in personality and social psy-chology: 291–326. Hillsdale, NJ: Erlbaum.

Levy, P. E., Cober, R. T., & Miller, T. 2002. The effect oftransformational and transactional leadership per-ceptions on feedback-seeking intentions. Journal ofApplied Social Psychology, 32: 1703–1711.

Little, T. D., Cunningham, W. A., & Shahar, G. 2002. Toparcel or not to parcel: Exploring the question,weighing the merits. Structural Equation Modeling,9: 151–173.

MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M.,West, S. G., & Sheets, V. 2002. A comparison ofmethods to test mediation and other interveningvariable effects. Psychological Methods, 7: 83–104.

Madjar, N., Oldham, G. R., & Pratt, M. G. 2002. There’s noplace like home? The contributions of work andnonwork creativity support to employees’ creativeperformance. Academy of Management Journal,45: 757–767.

Madjar, N. 2005. The contributions of different groups ofindividuals to employees’ creativity. Advances inDeveloping Human Resources, 7(2): 182–206.

McKinnel Jacobson, C. 1993. Cognitive styles of creativ-ity: Relations of scores on the Kirton Adaptation-Innovation Inventory and the Myers-Briggs Type In-dicator among managers in the USA. PsychologicalReports, 72: 1131–1138.

Miller, V. D., & Jablin, F. M. 1991. Information seekingduring organizational entry: Influences, tactics, anda model of the process. Academy of ManagementReview, 16: 92–120.

Milliken, F. J., & Martins, L. L. 1996. Searching for com-


mon threads: Understanding the multiple effects ofdiversity in organizational groups. Academy ofManagement Review, 21: 402–433.

Morrison, E. W., & Bies, R. J. 1991. Impression manage-ment in the feedback-seeking process: A literaturereview and research agenda. Academy of Manage-ment Review, 16: 522–544.

Morrison, E. W., & Weldon, E. 1990. The impact of anassigned performance goal on feedback-seeking be-havior. Human Performance, 3(1): 37–41.

Morrison, E. W. 1993. Newcomer information seeking:Exploring types, modes, sources, and outcomes.Academy of Management Journal, 36: 557–589.

Morrison & Vancouver. 2000.

Nonaka, I. 1994. A dynamic theory of organizational knowl-edge creation. Organization Science, 5: 14–37.

Northcraft, G. B., & Ashford, S. J. 1990. The preservationof self in everyday life: The effects of performanceexpectations and feedback context on feedback in-quiry. Organizational Behavior and Human Deci-sion Processes, 47: 42–xx.

Ohlsson, S. 1992. Information-processing explanations ofinsight and related phenomena. In M. T. Keane & K. J.Gilhooly (Eds.), Advances in the psychology of think-ing, vol. 1: xxx–xxx. London: Harvestor-Weathsheaf.

Oldham, G. R., & Cummings, A. 1996. Employee creativ-ity: Personal and contextual factors at work. Acad-emy of Management Journal, 39: 607–634.

Parker, S. K., & Collins, C. G. 2010. Taking stock: Inte-grating and differentiating multiple proactive behav-iors. Journal of Management, 36: 633–662.

Paulus, P. B., Larey, T. Z., & Dzindolet, M. T. 2001.Creativity in groups and teams. In M. Turner (Ed.),Groups at work: Advances in theory and research:319–338. Mahwah, NJ: Erlbaum.

Paulus, P. B. 2008. Fostering creativity in groups andteams. In J. Zhou & C. E. Shalley (Eds.), Handbook oforganizational creativity: 165–188. New York: Erlbaum.

Perry-Smith, J. E., & Shalley, C. E. 2003. The social side ofcreativity: A static and dynamic social network per-spective. Academy of Management Review, 28: 89–106.

Perry-Smith, J. E. 2006. Social, yet creative: The role ofsocial relationships in facilitating individual creativ-ity. Academy of Management Journal, 49: 85–101.

Perry-Smith, J. E. 2008. When being social facilitatescreativity: Social networks and creativity within or-ganizations. In J. Zhou & C. E. Shalley (Eds.), Hand-book of organizational creativity: 189–210. NewYork: Erlbaum.

Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsa-koff, N. P. 2003. Common method biases in behav-ioral research: A critical review of the literature andrecommended remedies. Journal of Applied Psy-chology, 88: 879–903.

Porath, C. L., & Bateman, T. S. 2006. Self-regulation:From goal orientation to job performance. Journal ofApplied Psychology, 91: 185–192.

Preacher, K. J., & Hayes, A. F. 2008. Asymptotic andresampling strategies for assessing and comparingindirect effects in multiple mediator models. Behav-ior Research Methods, 40: 879–891.

Raelin. 1997. A model of work-based learning. Organi-zation Science, 8: 563–578.

Rhoades, L., & Eisenberger, R. 2002. Perceived organiza-tional support: A review of the literature. Journal ofApplied Psychology, 87: 698–714.

Rogelberg, S. G., 2002. Handbook of research methodsin industrial and organizational psychology. Lon-don: Blackwell.

Ruscio, J., Whitney, D. M., & Amabile, T. M. 1998. Look-ing inside the fishbowl of creativity: Verbal and be-havioral predictors of creative performance. Creativ-ity Research Journal, 11: 243–263.

Scott, S., & Bruce, R. 1994. The influence of leadership,individual attributes, and climate on innovative be-havior: A model of individual innovation in theworkplace. Academy of Management Journal, 37:580–607.

Shalley, C. E. 1991. Effects of productivity goals, creativ-ity goals, and personal discretion on individual cre-ativity. Journal of Applied Psychology, 76: 179–185.

Shalley, C. E., Gilson, L. L., & Blum, T. C. 2009. Interactiveeffects of growth needs strength, work context, and jobcomplexity on self-reported creative performance.Academy of Management Journal, 52: 480–505.

Shalley, C. E., & Perry-Smith, J. E. 2001. Effects of social-psychological factors on creative performance: Therole of informational and controlling expected eval-uation and modeling experience. OrganizationalBehavior and Human Decision Processes, 84: 1–22.

Shalley, C. E., Zhou, J., & Oldham, G. R. 2004. The effectsof personal and contextual characteristics on creativ-ity: Where should we go from here? Journal of Man-agement, 30: 933–958.

Shalley, C. E., & Liu, Y. 2007. The effects of creativitygoals, verbal and monetary rewards on creativity.Working paper, Georgia Institute of Technology.

Shalley, C. E. 2008. Creating roles: What managers can doto establish expectations for creative performance. InJ. Zhou & C. E. Shalley (Eds.), Handbook of organ-izational creativity: 147–164. New York: Erlbaum.

Shalley, C. E., & Zhou, J. 2008. Organizational creativityresearch: A historical overview. In J. Zhou & C. E.Shalley (Eds.), Handbook of organizational creativ-ity: 3–31. New York: Erlbaum.

Shin, S. J., & Zhou, J. 2003. Transformational leadership,conservation, and creativity: Evidence from Korea.Academy of Management Journal, 46: 703–714.


Snyder, M. 1974. Self-monitoring of expressive behavior.Journal of Personality and Social Psychology, 30:526–537.

Steelman, L. A., Levy, P. E., & Snell, A. F. 2004. Thefeedback environment scale: Construct definition,measurement, and validation. Educational and Psy-chological Measurement, 64: 165–184.

Stine, R. 1989. An introduction to bootstrap methods.Sociological Methods and Research, 18: 243–291.

Tierney, P. 2008. Leadership and employee creativity. InJ. Zhou & C. E. Shalley (Eds.), Handbook of organ-izational creativity: 95–123. New York: Erlbaum.

Tierney, P., & Farmer, S. M. 2002. Creative self-efficacy:Its potential antecedents and relationship to creativeperformance. Academy of Management Journal,45: 1137–1148.

Tierney, P., Farmer, S. M., & Graen, G. B. 1999. Anexamination of leadership and employee creativity:The relevance of traits and relationships. PersonnelPsychology, 52: 591–620.

Tsui, A. S., & Ashford, S. J. 1994. Adaptive self-regula-tion: A process view of managerial effectiveness.Journal of Management, 20: 93–121.

Tsui, A. S., Ashford, S. J., St. Clair, L., & Xin, K. R. 1995.Dealing with discrepant expectations: Responsestrategies and managerial effectiveness. Academy ofManagement Journal, 38: 1515–1543.

Vancouver, J. B., & Morrison, E. W. 1995. Feedback in-quiry: The effect of source attributes and individualdifferences. Organizational Behavior and HumanDecision Processes, 62: 276–285.

VandeWalle, D., Brown, S. P., Cron, W. L., & Slocum,J. W. J. 1999. The influence of goal orientation andself-regulation tactics on sales performance: A lon-gitudinal field test. Journal of Applied Psychology,84: 249–259.

VandeWalle, D., Ganesan, S., Challagalla, G. N., & Brown,S. P. 2002. An integrated model of feedback-seekingbehavior: Disposition, context, and cognition. Jour-nal of Applied Psychology, 85: 996–1003.

Van Der Vegt, G. S., Van De Vliert, E., & Oosterhof, A.2003. Informational dissimilarity and organizationalcitizenship behavior: The role of intrateam interde-pendence and team identification. Academy ofManagement Journal, 46: 715–727.

Vohs, K. D., & Baumeister, R. F. 2004. Understandingself-regulation. In R. F. Baumeister & K. D. Vohs(Eds.), Handbook of self-regulation: 1–9. New York:Guilford.

Wayne, S. J., Shore, L. M., & Liden, R. C. 1997. Perceivedorganizational support and leader-member ex-change: A social exchange perspective. Academy ofManagement Journal, 40: 82–111.

West, M. A., & Richter, A. 2008. Climates and cultures forinnovation and creativity at work. In J. Zhou & C. E.

Shalley (Eds.), Handbook of organizational creativ-ity: 211–236. New York: Erlbaum.

Williams, J. R., Miller, C. E., Steelman, L. A., & Levy, P. E.1999. Increasing feedback seeking in public con-texts: It takes two (or more) to tango. Journal ofApplied Psychology, 84: 969–976.

Woodman, R. W., Sawyer, J. E., & Griffin, R. W. 1993.Toward a theory of organizational creativity. Acad-emy of Management Review, 18: 293–321.

Yuan, F., & Woodman, R. W. 2010. Innovative behaviorin the workplace: The role of performance and imageoutcome expectations. Academy of ManagementJournal, 53: 323–342.

Zhou, J. 1998. Feedback valence, feedback style, taskautonomy, and achievement orientation: Interactiveeffects on creative performance. Journal of AppliedPsychology, 83: 261–276.

Zhou, J., & George, J. M. 2001. When job dissatisfactionleads to creativity: Encouraging the expression of voice.Academy of Management Journal, 44: 682–696.

Zhou, J. 2003. When the presence of creative coworkersis related to creativity: Role of supervisor close mon-itoring, developmental feedback, and creative person-ality. Journal of Applied Psychology, 88: 413–422.

Zhou, J. 2008. Promoting creativity through feedback. In J.Zhou & C. E. Shalley (Eds.), Handbook of organiza-tional creativity: 125–145. New York: Erlbaum.

Katleen E. M. De Stobbeleir ([email protected]) is an assistant professor of organizational behaviorand leadership at Vlerick Leuven Gent ManagementSchool and a research fellow at K.U. Leuven. She earnedher ICM-Funded Ph.D. in applied economics from GhentUniversity. Her current research focuses on leadershipstructure schemata and employee proactivity in the var-ious stages of the creative process (i.e., idea generation,idea promotion, and idea implementation).

Susan J. Ashford ([email protected]) is the Michael andSusan Jandernoa Professor of Business Administrationand a professor of management and organizations at theRoss School of Business, University of Michigan. Hercurrent research focuses on individual proactivity, socialprocesses of leadership construction, job insecurity, andissue selling in organizations.

Dirk Buyens ([email protected]) is a professor ofhuman resources management at Vlerick Leuven GentManagement School and at Ghent University. He earnedhis Ph.D. in industrial and organizational psychology atGhent University. His current research focuses on em-ployer branding, strategic human resources management,and human resources practices that foster creativity inorganizations.


Copyright of Academy of Management Journal is the property of Academy of Management and its content may

not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written

permission. However, users may print, download, or email articles for individual use.

self-regulation of creativity at work: the...

Documents