A contribution to a multilevel theory of creativity

Geert Vissers & Ben Dankbaar

In: J.J. Chanaron, E. Carayannis (eds.), Managing Creative People (working title), MacMillan, forthcoming

Introduction

Creativity research has become an accepted branch of management and organization studies, encouraged by the increased importance of innovation research (West & Farr 1990; Drazin & Schoonhoven 1996; Ford 1996; Bourguignon & Dorsett 2002). In the process, creativity research has adapted to the organization as a research object – which is notably different from individuals as used to be studied. Woodman et al. (1993: 315) simply note that “Research on organizational creativity will by definition cross multiple levels of analysis.” Accordingly, a ‘multilevel’ approach has been developed that focuses on issues of ‘individuals in context’ (Woodman et al. 1993; Ford 1996; Drazin et al. 1999). The approach is important, serving as a conceptual framework for the study of creativity in organizations, but is still rooted in psychological creativity research. In particular, creativity continues to be associated with individuals, and idea generation tends to be treated as a single-level achievement rather than a process that involves a sequence of steps involving various levels.

In this chapter, we will show that various forms of collective creativity are conceivable, or even likely, and that recognition of these will improve the prospects of a multilevel approach to organizational creativity. It appears that the reluctance to accept collective creativity derives from the lack of support for group level creativity in brainstorming research, a field of work that was inspired by psychological approaches to creativity. In a first section we will offer a brief description of these psychological approaches. The second section presents a discussion of brainstorming research. We will argue that the well-known conclusion that individuals working separately generate more, and more creative ideas than do groups (McGrath 1984: 131) is premature. In the third section we return to the study of creativity in organizations, in a way that agrees with Zhou and Shalley’s (2003: 206) claim that models of work group or team creativity should be developed.

1. Psychological approaches to creativity

Creativity has long been the domain of psychological research (Ford 1996). It was a field of study in which seminal contributions to art or science were investigated, but

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also ‘ordinary’ contributions to other fields of activity, which inspired Stein to make a distinction between ‘Big C’ and ‘small c’ creativity (Kaufmann 2004: 158; Simonton 2002: 180). In our view, the study of creativity has been dominated by two debates, one between ‘creativity as an activity (or capacity to act)’ and creativity as an outcome of activity’ – between ‘process’ and ‘product’ in Rhodes’ terms (Rhodes 1961/1978; Couger et al. 1993: 377-380; El-Murad & West 2004; Runco 2005: 661), and a second between creativity as a general versus creativity as a domain-specific phenomenon. In the present section we will review these debates, treating the product versus process debate as part of a discussion of creativity measurement – which some authors believe to be the most critical issue in creativity research (Magyari-Beck 1997).

Generality versus domain-specifici y. t

Whether creativity refers to general or domain-specific abilities and activities is a question that reflects a similar discussion in educational psychology. In the field of creativity research the issue has been addressed explicitly by Plucker (1998), defending the ‘general creativity’ hypothesis and Baer (1998), defending the ‘domain-specific creativity’ hypothesis. This discussion is confined to the exchange of interpretations of quantitative studies.

Baer (1998) mentions recent studies of creative performance in which participants create more than one thing (poems, stories, mathematical puzzles, collages, drawings) and each artifact is judged for creativity by ‘appropriate experts’. He argues that “correlations among the creativity ratings of products made by the same person in these studies have been quite low, especially when the effects of differences in academic ability have been held constant statistically” (Baer 1998: 174) and that creativity is therefore not general, but domain-specific. This finding is not convincing. It deals with ‘products’ whereas the ‘general creativity’ hypothesis stresses basic cognitive abilities that are relevant for, particularly, children’s learning (Torrance 1993). As described by Olson (1989: 67), such abilities or ‘cognitive skills’ include basic operations of memory (e.g. association, recognition, and recall), skills to gain knowledge from experience (e.g. induction and categorization), and skills that recombine existing knowledge to form new knowledge (e.g. deduction, statistical reasoning, and analogical reasoning). ‘Making a collage’ or ‘solving a mathematical puzzle’ do not fit into one of these categories of cognitive skill. The low correlations between tasks may reflect domain-related differences in knowledge, experience, or preference (which have to be held constant if creativity is being examined). They may also represent the sensory mode differences proposed by Torrance (1980: 10) in a discussion of Lowenfeld’s notion of ‘modality strengths’. Torrance notes that “children rely on different sensory modes to help them in learning, thinking, and creating. Some depend heavily on their sense of sight, others on their sense of hearing, and still others on their kinesthetic senses.” It is possible that Baer’s findings must be ascribed to such differences. In any case, the mere

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finding that those who are creative in writing poems (nice poems, unusual poems, thoughtful poems?) are less creative in solving (or making?) mathematical puzzles is, at best, weak evidence in favor of a ‘domain-specific creativity’ hypothesis.

Plucker’s (1998) arguments in favor of the ‘general creativity’ hypothesis are barely more convincing. Discussing theoretical arguments, Plucker (1998: 180) relies on Anderson et al. (1996) who make the case against the view that knowledge and skills are fully situated. Precisely this is what the discussion lacks most: The recognition that the issue is not whether knowledge and learning – and creativity, by implication – are general or domain-specific, but how general and domain-specific knowledge are interrelated, and how one is necessary to acquire the other. In his discussion of ‘empirical evidence’ Plucker (1998: 181) makes the observation that researchers using the consensual assessment technique (a performance-based assessment method) usually support the position that creativity is predominantly task- or content-specific while traditional psychometric methods usually support the position that creativity is predominantly content general. This is not surprising. The consensual assessment technique, developed by Amabile, involves the use of judges who, basically, must be “familiar enough with the domain to have developed, over a period of time, some implicit criteria for creativity, technical goodness, and so on” (Amabile 1996: 42). Thus, the use of these judges introduces domain-specific knowledge as part of the research setting – which can only support the position that creativity is specific to a task or domain.

Likewise, it is natural that psychometric methods tend to support the position that creativity is content independent. Baer (1998: 173) suggests that psychologists are inclined towards general theories that could explain all kinds of creativity at once. Some psychologists are, perhaps, but it is only fair to acknowledge that many psychological tests are designed to be general or ‘context-free’ because they should be applicable in a broad range of situations without reproducing educational, socio-economical, or cultural differences. Creativity tests do not differ from other psychological tests in this respect: “Because it is desirable for social-psychological research that there not be large differences in baseline performances on the task, it should be one that does not depend heavily on special skills” (Hennessey & Amabile 1988: 15). Thus, psychometric methods are used in a research setting that carefully avoids to tap any form of domain-specific knowledge, experience, or skill – which is more than likely to produce support for the ‘general creativity’ hypothesis. (Note that the very attempt to develop ‘context-free’ tests reflects the awareness that domain-specific knowledge, experiences, and skills do exist, and are strong enough to influence test results systematically.)

In short, the arguments presented by Plucker and the arguments presented by Baer do not converge. Not mentioned by either author is the argument that creativity is special, as compared to knowledge and learning in general: It requires recognition by others (Csikszentmihalyi 1999; Simonton 2003). In this regard, ‘domains’ can be very different, as a narrative by Csikszentmihalyi (1988) may demonstrate. It is the

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story of a famous physicist who was giving a lecture in Munich, to find his blackboard presentation interrupted by a student who ‘jotted down’ a formulation of the equation that was different from the formulation developed by the physicist himself. The student’s formulation was more elegant and suggestive than the professor’s. Soon, the story continues, all theoretical physicists in Germany knew of the event and within a month American physicists had started to give the new equation a try. Eventually the student was to receive a Nobel Prize. According to Csikszentmihalyi, such a reception of a new idea would be inconceivable within psychology.

The story implies that the perception of creativity is contingent with the cognitive structuring of a domain (e.g. a scientific discipline), and suggests that different domains do not associate the same behaviors (or ‘products’) with creativity. This means (under the assumption that creativity is an individual achievement), that the same type of behavior may give rise to different judgments of creativity in different domains, and that recognition as an expert in one discipline may require other behaviors than recognition as an expert in a second discipline. It can be gathered that a discussion of general versus domain-specific creativity should not assume patterns of recognition to be similar across domains. This conclusion does not rule out the possibility that a single person is capable of different behaviors that are judged as creative in different domains (see Kasof’s (1995: 321-22) discussion of ‘distinctiveness’, that is generalization across situations).

Big C versus little c creativity

The study of ‘Big C’ creativity, in the form of studies of historical individuals (and the achievements that made them historical), used to be an important part of creativity research. This seems no longer the case. Barron and Harrington (1981: 463-466) could mention a large number of studies devoted to ‘psychobiography, psychohistory, and the life-span perspective’, but Runco (2005: 678), in his update to this review, simply observes that “creativity is now viewed as something that can be found and used in an ‘everyday’ domain.”

That the study of historical individuals has largely disappeared (Simonton is one of the few scholars left in this field, see Simonton 1999) may relate to the problem to disentangle personal and social factors in the case of grand scientific contributions. The difficulty is increased by phenomena that are unlikely to be associated with creativity, such as the use of ‘fudged’ data by renowned historical figures like Newton and Mendel (Eysenck 1993: a reply to Barron), and recognition processes that reflect a ‘Matthew effect’ – a term referring to St. Matthew’s Gospel: “every one that hath shall be given, and he shall have abundance”, now meaning that famous scientists are more likely to be quoted than others (Merton 1968; Henrickson 2003).

However, the disappearance of Big C studies is not without costs. First, it deprives creativity research of a branch of work that has its own appeal and often reaches the

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general public. Second, it deprives creativity research of a line of research that might counteract ‘easy’, short term-oriented conceptions of creativity like ‘new and useful’ – which is consistent with Csikszentmihalyi and Sawyer’s (1995) view that big C Creativity involves a long and small c creativity a short time span. Third, it deprives creativity research of an important incentive to consider degrees of creativity. This comment is in agreement (though the words are different) with Harrington’s (2004) remark that there is a large and important middle range of creativity (‘middle c’ creativity): creative acts that have a significant social impact, but without transforming entire fields of human endeavor. Fourth, it deprives creativity research of some highly relevant research questions: Whether Big C and small c creativity are qualitatively or quantitatively distinct (Simonton 2002: 195), whether Big C may serve as an exemplar for small c or middle c creativity, and whether small c creativity is a possible start of a process leading to middle c or even Big C creativity.

The measurement of creativity

In 1950, J.P. Guilford gave a presidential address titled ‘Creativity’ to the American Psychological Association, that came to be viewed as the ‘official’ launch of creativity research. Guilford was a psychometrician who studied creativity as one among several other ‘intellectual factors’. In his address, he advocated the use of open questions: “I do not now see how some of the creative abilities, at least, can be measured by means of anything but completion tests of some kind. To provide the creator with the finished product, as in a multiple-choice item, may prevent him from showing precisely what we want him to show: his own creation” (Guilford 1950: 445).

Guilford’s view has been very influential, inspiring a large number of studies of individual differences in the capacity for idea generation. Mumford and Gustafson (1988: 32) note that these studies usually focused on Guilford’s (1950) divergent thinking construct, an observation that seems accurate except that the phrase ‘divergent thinking’ did not appear in Guilford’s 1950 article. This phrase denotes an individual’s ability to generate multiple potential solutions to a problem, an ability that is “typically measured by presenting individuals with an open-ended stimulus problem to which they are required to generate as many solutions as possible” (Mumford & Gustafson, op. cit.).

Over the years many divergent thinking tests have been developed (see Eysenck 1994; Plucker 1999; Plucker & Renzulli 1999; Runco 2005), some of which are still widely used. These tests have been the subject of persistent criticism, however. Prominent are the objections raised by Amabile (1983; 1996). She discusses validity problems, “especially troublesome since many of the creativity tests are validated against one another” (Amabile 1996: 27), designation problems (verbal fluency should not be called ‘originality’), unjustified objectivity claims, and the fact that tests tend to be used for other, more ambitious purposes than those for which they were designed. The last remark refers to the fact that many tests were designed for

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measuring individual differences in particular personality traits, often for use in educational settings, but have later been used in experimental studies of factors influencing general creativity. In a review that is in support of divergent thinking tests, Plucker (1999) discusses the general comment that the predictive value of such tests is insufficient, which he relates to the fact that often a single measurement research design is used instead of a longitudinal design, and to the fact that the (non-normal) distributions of divergent thinking test outcomes are not always treated properly. Other comments have been made that include the artificial nature of tasks in the context of divergent thinking tests (Amabile 1996: 172; Plucker & Runco 1998), the culture-dependence of divergent thinking tests (Chen et al. 2002: 172), or the neglect of domain differences, as in Simonton’s (2002) remark that creativity in music is not going to be very predictable on the basis of how many uses one can imagine for a toothpick. Finally, an implicit but important comment is Mumford’s (2003: 149) warning against too much emphasis on potential creativity. His argument is that a focus on outcomes makes it possible to take domain effects, situational influences, and population characteristics into account.

This criticism has paved the way for various new measurement techniques, of which Amabile’s (1996, chapter 3) consensual assessment technique is the most prominent. Note, however, that this technique involves outcomes (or ‘product’) and is therefore not directly comparable to divergent thinking tests, which involve personal traits. Amabile stresses that the technique relies on ‘real life’ tasks, as opposed to the more artificial, sometimes closed tasks used in creativity tests (for a discussion of open vs. closed tasks, see Unsworth 2001).

It is unclear if the consensual assessment technique can be used in the case of ‘ill-defined problems’, which are problems with various possible goals, various possible problem-solving trajectories, and various possible solutions. The relevance of this type of problems is stressed by Hayes (1990), Mumford (2003), and Reiter-Palmon & Illies (2004), and associated by Gallagher (1994: 174) with the neglected issue of ‘problem finding’. Another issue is the value of expert judgment (or of judgment in general) in settings in which nothing is at stake. The question is whether judges’ assessments within the confines of a research setting have sufficient external validity. While this subject is poorly addressed (for a remote example see Ebbesen & Konecki 1980), the subject is urgent since Nemeth et al. (2001) demonstrated the importance of ‘authentic’ (as opposed to ‘played’) views.

Finally, Amabile’s technique has been subjected to straightforward critique by Magyari-Beck (1997). The argument is that highly creative contributions (the example given is Giordano Bruno’s contribution to Sixteenth Century science) would not pass the test of consensual assessment by contemporaries. The conclusion, therefore, must be “that something can be creative either if it is accepted by the ‘consensual assessment technique’ or if it is rejected by the ‘consensual assessment technique’” (Magyari-Beck 1997: 61).

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To summarize, in this section we have given an overview of psychological approaches to creativity. It is not meant to be complete regarding the lines of research that have been followed, nor regarding to developments within any particular line of research, but our discussion shows: firstly, that some important issues with psychological creativity research have not been brought to a closure; secondly, that research is largely focusing on idea generation capabilities at the expense of selection processes (which implies that ‘ideas’ are only conceived of as the result of a single ‘cognitive loop’); and thirdly, that psychological creativity research tends to make no reference at all to groups or other ‘collective actors’ that may play a part in idea generation or idea selection.

In the following two sections we present a line of argument in defense of creativity as a more social and more iterative phenomenon than psychological creativity research is able to accept. The argument starts from the observation that the notion of organizational creativity requires the recognition that creative activity does not take place in social isolation (Drazin et al. 1999: 293), or in a vacuum – to adopt an expression used by Guilford (1950: 448), Kurtzberg & Amabile (2000: 287), Mumford (2000: 314), Shalley & Gilson (2004: 35). As described in the third section, multilevel accounts of organizational creativity have been developed accordingly. Authors providing such accounts, however, seem reluctant to include a notion of collective creativity, which can be ascribed to views stemming from brainstorming research.

Brainstorming research is a field that has never been central in psychological creativity research, but as a field of social psychological research it was adjacent. In particular, tests were used in brainstorming research that had been derived from psychological creativity research, such as the ‘Consequences Test’ and the ‘Unusual Uses Test’, both developed under Guilford’s auspices (see Meichenbaum 1975; Eysenck 1994). These tests, aiming to be context-free, provide tasks as ‘‘name as many uses as you could think of, for a toothpick” (Unusual Uses Test), or “what would happen if everyone born after the year 2000 had an extra thumb on each hand” (Consequences Test).

In management and organization studies, brainstorming research was relatively well-known, and brainstorming itself a broadly used idea generation technique (Nijssen & Lieshout 1995; Sutton & Hargadon 1996). Brainstorming research was probably the field in which individual- versus group-level comparisons were most visible. After a period of research in support of brainstorming – a group-level technique – the conclusion was arrived at that brainstorming does not work, and even has detrimental effects. This conclusion, that was widely adopted, has effectively discouraged the study of collective creativity. Before outlining the argument of creativity as a social and iterative phenomenon we will in the next section present a discussion of brainstorming research, arguing that the available research does not justify a rejection of group creativity on the basis of brainstorming research..

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2. Research on the effectiveness of brainstorming

There is a close link between creativity and idea generation, regardless of what these terms are taken to mean exactly. Any definition of creativity includes the notion of newness – usually new ideas – and these ideas have to be generated. It is not surprising, then, that group creativity is readily associated with brainstorming, which is the best known and the most widely used technique for group idea generation (Fernald & Nicolenko 1993; Isaksen 1998). Puccio (1999: 640) notes that “Research that has specifically examined group creativity has been limited primarily to the validation of one creative problem-solving tool – namely, brainstorming.” Although the word ‘brainstorming’ is now often used in ways departing from the concept’s original meaning (Isaksen 1998), brainstorming is still frequently seen as an approximation of group creativity. Many articles in the field of brainstorming research point at the large and growing need for creativity in the world of management and organizations (Paulus et al. 2000). As a justification of research this claim is not very accurate, since brainstorming seems to serve more purposes than idea generation alone (Sutton & Hargadon 1996; Kramer et al. 1997). The rationale of brainstorming, according to Paulus (1999: 780), is that the ability to take new or unusual responses to problems may require “a somewhat random association of different domains, sets of knowledge, or ideas. Group interaction should be ideal for such a process.”

History of b ainstorming resea ch r r

Group brainstorming, introduced by Osborn (1953), was an early attempt to systematically utilize the creative potential of groups. The method, even though it has been criticized for being poorly defined (Crosby 1968: 35), must be distinguished from ‘unstructured brainstorming’ (VanGundy 1984: 16; Sutton & Hargadon 1996: 715). It involves four key rules: (1) Criticism is ruled out; defer all judgment; (2) Freewheeling is welcome; the wilder the ideas, the better; (3) Quantity is wanted; the more wild ideas, the better; (4) Hitchhiking and combination are sought; when possible, build on previous ideas to produce new ones. (VanGundy 1984: 111; Isaksen 1998: 4)

In the first editions of his book, Osborn claimed that adherence to his rules would more than double the ideas of group members. This claim provoked a series of experimental studies on the effectiveness of brainstorming in groups (Sutton & Hargadon 1996: 686, n1). Two types of comparison were made in particular. The first was between groups that do and groups that do not separate the production of ideas from the evaluation of these ideas. It was found that deferring of judgment does actually contribute to both quality and quantity of ideas (Vennix 1996: 167). The second comparison was between interacting and non-interacting (or ‘nominal’) groups, which refers back to the rule that group members build on previous ideas. Here, many studies reported evidence in favor of nominal group brainstorming, especially when idea quantity was used as a criterion (Diehl & Stroebe 1987: 498).

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Apparently, the issue was settled by the time McGrath (1984) noted that “Most of the comparison studies have compared groups using brainstorming techniques to individuals using brainstorming techniques. For this comparison, the evidence speaks loud and clear: individuals working separately generate many more, and more creative (as rated by judges) ideas than do groups, even when the redundancies among member ideas are deleted, and, of course, without the stimulation of hearing and piggybacking on the ideas of other. The difference is large, robust, and general.” (McGrath 1984: 131)

McGrath’s conclusion was followed by studies that tried to answer why precisely individuals performed better than groups (Furnham & Yazdanpahani 1995: 73). An important contribution to this line of research was a study by Diehl and Stroebe (1987). The study did not question the finding that nominal brainstorming groups outperform interacting brainstorming groups, but tested three main hypotheses that had been offered to explain the poor idea-generation capacities of interacting groups. A first hypothesis referred to ‘production blocking’: in an interacting group only one member can speak at a time, to the effect that other members “are prohibited from verbalizing their ideas as they occur, may forget or suppress them because they seem less relevant or less original at a later time. Finally, being forced to listen to the ideas of other group members may prove distractive and interfere with the subjects’ own thinking.” (Diehl & Stroebe 1987: 498) A second hypothesis stressed evaluation apprehension: “Despite brainstorming instructions, the fear of negative evaluations from other group members prevents subjects who are working in groups from presenting their more original ideas” (Op. cit.). A third hypothesis focused on effort reduction: individuals in interacting groups may reduce their efforts when monitoring of these efforts is perceived to be inadequate or when they feel that their own contribution is dispensable. In a series of experiments production blocking was found to have the strongest effect, and it was recommended “to ask subjects first to develop their ideas in individual sessions and next have these ideas discussed and evaluated in a group session.” (Diehl & Stroebe 1987: 508)

Following Diehl and Stroebe’s (1987) article, brainstorming came to be seen as a poor instrument for idea generation in groups, even to the effect that “scholars and textbooks in social psychology and organizational behavior usually conclude that group brainstorming or generating ideas in groups is not a good idea if one wants to obtain many ideas” (Paulus 2000: 241). Still, efforts were made to improve group brainstorming (Paulus 2000; Kramer et al. 2001). The argument was that trying to improve a widely used instrument does make sense, especially if this instrument is still believed to have the potential of producing ideas that are unlikely to be generated by individuals brainstorming (Brown & Paulus 2002). There was reason to believe that such attempts would be successful. Experiments had produced a variety of suggestions for improving group performance (Nijstad et al. 2003) and, in addition, measures that seemed useful were found to have a negative effect on group performance: group goal setting and selecting individuals with a preference for working in groups. The latter finding was disturbing as it was also found that

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anxiousness – participants feeling uncomfortable with group interaction – also hampers group performance. Clearly, the composition of brainstorming groups is important (Paulus et al. 2000).

More or less separately, electronic group brainstorming (EBS) emerged as a field of study. EBS concerns the use of a computer network that allows ideas to be entered, facilitates the sharing of ideas with other group members, and supports group evaluation of the ideas generated. EBS seemed promising: when individuals are able to express their ideas using a keyboard they do not have to wait for others, which prevents production blocking. And if software is used that enables an individual to inspect the ideas generated by others, the generation of redundant ideas may be avoided and individuals may still be inspired by others’ ideas. Moreover, EBS systems can offer the anonymity needed to prevent evaluation apprehension. Thus, electronic brainstorming was welcomed as a procedure that would eliminate all the factors that, according to Diehl and Stroebe, produced process loss in brainstorming groups (Guzzo & Dickson 1996; Barki & Pinsonneault 2001). Indeed, electronic brainstorming groups were found to outperform traditional brainstorming groups, (Gallupe et al. 1992; Dennis & Valacich 1993). Later research, however, did not meet the initial promise of EBS (Pinsonneault et al. 1999; Potter & Balthasard 2004). Recent studies suggest convergence, that is, the use of electronic means is treated as a factor among many others that may help to overcome process loss in brainstorming groups.

It is unclear whether the findings arrived at in experimental brainstorming research apply to group creativity in real life settings: “Because most of the controlled studies have used ad hoc and untrained groups of students generating ideas on topics of little personal relevance, generalization to organizational settings may be unwarranted.” (Paulus et al. 2000: 320) An inventory of differences between brainstorming under laboratory conditions and brainstorming in organizational settings (Paulus et al. 2000; Isaksen 1998) suggests that such generalization refers to the application in organizational settings of brainstorming as an idea-generation technique. If however ‘group creativity’ is the domain of reference (instead of ‘group brainstorming for the purpose of generating ideas’), it is necessary to consider how processes of newness generation in organizations actually happen. Typically, such processes do not rely on contributions made by ad hoc groups, they do not involve the kind of tasks frequently used in brainstorming research, and they are not confined to producing as many ideas as possible within a limited time span. We will briefly examine these three subjects

Type of groups: Few organizational workgroups are as instant as the groups typically used in experimental research. “There may be some natural groups that do exist only for a single meeting and work on only a single topic, but by far the majority of natural groups have a life that extends beyond a single meeting on a single topic” (McGrath & Hollingshead 1994: 76). Similarly, Sutton and Hargadon (1996: 688) observe that “nearly all brainstorming research was done with participants who (1)

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had no past or future task interdependence; (2) had no past or future social relationships; (3) didn’t use the ideas generated; (4) lacked pertinent technical expertise; (5) lacked skills that complement other participants; (6) lacked expertise in doing brainstorming; and (7) lacked expertise in leading brainstorming sessions.” The use of such ‘instant groups’ violates Osborn’s rules (Isaksen 1998) and ignores that for group productivity gains to occur a realistic situation is required, more specifically a situation in which group members have interests to defend (Michaelsen et al. 1989). It also ignores that a group needs time before productivity gains may develop (Watson et al. 1993). Moreover, the groups typically used in experimental research are more homogeneous than their counterparts in real life (Paulus et al. 1995: 261; Watson et al. 1998). This homogeneity means that the knowledge base of experimental groups is relatively small, which is likely to preclude precisely the process gains that groups are supposed to achieve (Watson et al. 1998: 410; McGlynn et al. 1995: 68).

Nature of tasks. The tasks in brainstorming studies are often highly artificial, or even irrelevant and inconsequential (Harari & Graham 1975; Furnham & Yazdanpanahi 1996: 73; for an overview, see Brophy 1998: 213-215). While fitting in the context of laboratory research, the use of such tasks seems at variance with Osborn’s recommendations: “The problem had to be clearly stated and focused for idea generation. The task had to be specific rather than general. It should provide a single target for participants’ idea-generating efforts.” (Isaksen 1998: 5).

Pinsonneault et al. (1999) suggests the use of socially sensitive tasks, arguing that such tasks will help to keep individuals motivated, whereas motivation loss would cause the production of ideas to decrease. The argument is remarkable since there is evidence of a negative relationship between the use of realistic, important tasks and the number of ideas generated (Dillon et al. 1972; Harari & Graham 1975; Graham 1977). Considerable efforts have been made to explain this negative relationship in terms of the scheme proposed by Diehl and Stroebe (1987). However, the simple conclusion that ‘number of ideas generated’ is a poor indicator of creativity, or even of divergent thinking capacity, has not been drawn.

Focus on idea generation. Mumford et al. (2001: 2) note that studies of brainstorming groups rely on idea generation as a criterion measure: “More specifically, they have focused on fluency, or the number of ideas produced, in response to general, relatively simple problem scenarios.” Creative processes in a real life context, in contrast, involve problem finding, problem solving (idea generation and evaluation) and solution implementation as stages that are mutually influencing (Mumford et al. 2001). When the idea-generation stage is considered in isolation, as in brainstorming research, a method is needed to assess the quality of results, for there is no ‘naturally’ ensuing evaluation stage to be observed. This is why brainstorming studies (and other studies measuring creative performance) have to rely on psychometric methods or on expert judgment.

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Psychometric methods use quantitative data to evaluate divergent thinking performance in comparison to mean scores in a reference sample (Plucker & Runco 1998). Expert judgment is used to obtain performance rates, e.g. according to the consensual assessment technique. Both approaches have been discussed in the previous section. Important here is the observation that neither approach is able to assess the quality of ideas properly, for only the results of isolated idea generation are being examined. Therefore, brainstorming research has no defense against Gruber and Wallace’s (1999: 95) remark that “it is not self-evident how the ability to produce many ideas is related to the ability to produce a few superb ones.” The experimental format does not allow idea superbness to be recognized. Thus it is not possible to test Osborn’s claim that quality breeds quantity (Paulus 2000: 254).

To elaborate on the possibility of idea superbness, the notion of ‘idea’ must be considered first. If inventions are taken into account, which can be viewed as concrete, exemplary ideas, it appears that the word ‘idea’ is used to denote major discoveries in science and technology, but also an occasional suggestion made by a participant in a brief brainstorming session in response to some question about crime reduction, city planning, or the like. Even if such an idea is novel and useful, the organizational context required for assessment and refinement is not available. It is therefore confusing, if not misleading, to speak of ‘ideas’ in relation to what happens in a brainstorming session in the context of experimental research. And it is even more confusing to count these ideas, compare the numbers found in ‘real groups’ and in ‘nominal groups’, and draw the conclusion that organizational creativity is best served by individuals working alone, or working together in a computer environment that may help to prevent production blocking and other disadvantages of human interaction.

3. Creativity in organizations

In management and organization studies, the diffusion of the view that innovation requires creativity has given rise to ‘contextual’ theories of organizational creativity, according to which “it is the psychological meaning of environmental events that largely influences creative behavior” (Amabile et al. 1996: 1158). This recognition that factors outside the individual may contribute to creativity has given rise to many new research issues, which have been explored mostly with regard to employee creativity (Oldham & Cummings 1996; Zhou & Shalley 2003; Choi 2004), thereby confirming that organizational creativity is a relevant field of study. However, the contextual approach tends to adhere to an individualist view of creativity, because the approach has important roots in psychological creativity research, but also because a discouraging picture of group creativity is derived from brainstorming research. Indeed, several authors connect the notion of group creativity with brainstorming research (Woodman et al. 1993: 303; Paulus 2000: 241; Simonton 2002: 196; Zhou & Shalley 2003: 206; Nemeth et al. 2004: 366; Kurtzberg 2005: 53).

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Although some authors in the contextual tradition have noted that the group focus should be given more attention (Kurtzberg & Amabile 2000: 289; Zhou & Shalley 2003: 206), the possibility of ‘genuine’ group or organizational creativity has largely been ignored in this field of work. As a result, there is only a weak connection between the contextual approach and the view, widespread in management and organization studies, that groups, teams, and organizations are capable of knowing and learning (Argote et al. 1990; Weick & Roberts 1993; Miner & Mezias 1996; Glynn 1996; Edmondson 2002; For a critique of the notion of ‘organizational learning’ see Pavitt 2003).

In an attempt to develop a conceptual framework for the study of creativity in organizations, Woodman et al. (1993) proposed a ‘multilevel’ approach, a suggestion taken over by Ford (1996), Drazin et al. (1999), and Pirola-Merlo and Mann (2004). However, these studies tend to use the phrase ‘group creativity’ in a restricted sense, primarily considering creative group performance as an aggregate effect of creative performance by the individuals who consitute the group. Woodman et al. (1993: 304) note that “Group creativity is not the simple aggregate of all group members' creativity, although group creativity is clearly a function of the creativity of individuals in the group.” Starting from an perspective that views the creative behavior of organizational participants as a complex person-situation interaction, influenced by past events and by aspects of the current situation, the authors provide an impressive list of group and organization-level aspects that may have an impact on individuals’ creative behavior, but they do not discuss the possibility of creative behavior by a group that is sui generis in a Durkheimian sense: emerging from, but not to be reduced to the activity of individuals (Sawyer 2002: 231ff). Pirola-Merlo and Mann (2004) extend this line of work, arguing that a focus on individual-level creativity may lead to atomistic fallacy while a focus on team-level creativity cannot disclose the micro-level mechanisms that constitute team-level relationships. They propose a multi-level model of creative processes in teams as influenced by ‘team climate’ (West 1990). According to this view, new ideas are provided by individuals, and group creativity emerges from subsequent interaction between team members on the basis of these ideas. The multi-level model of team creativity that is presented views team creativity as the ‘simple aggregate of individual creativity’, which is “not (meant) to disprove the view that group creativity is synergistic in nature, but rather to show that alternative explanations are also consistent with existing evidence” (Pirola-Merlo & Mann 2004: 239).

Ford (1996), seeking to integrate psychological theories of creativity and sociological theories of innovation, distinguishes four levels that have an impact on individual creativity: groups/subunits, organizations, institutional environments, and markets. Drawing on Campbell’s (1960) evolutionary model of creativity, he proposes a view that describes the variation and selection processes that define creative actions in specific social domains (as described by Csikszentmihaly (1988): the rules, language, and customary practices of an area of action). Variation (creative action) results from an individual’s perception that habitual actions are no longer attractive. Selection is

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rather social in nature. Csikszentmihalyi’s (1988) concept of ‘field’ (the people who populate and effect the structure of a domain) is used to observe “that fields select variations produced by individuals and that selected variations become incorporated into the language and practice of a domain. Therefore, the influence of each domain can be described primarily in terms of the selection processes utilized by its respective field.” (Ford 1996: 1126)

The theory proposed by Drazin et al. (1999) is less restrictive with regard to ‘group creativity’ or ‘collective creativity’, but still preserves a prominent role for individual creativity. Unlike Ford (1996), who suggests that expected ‘economic’ advantage makes individuals engage in creative action, Drazin et al. (1999: 287) emphasize an individual's psychological engagement in creative action – “regardless of whether the resultant outcomes are novel, useful, or creative.” The authors take this viewpoint because they consider the relationship between creativity ‘as a choice made by an individual’ and ‘creativity as judged by others’ to be weak (Drazin et al. 1999: 290; 2000: 286), and because they reject static models that seek to explain variance in a dependent variable (creative outcomes); the likely result of researchers’ tendency to define creativity as an outcome (Drazin et al. 1999: 289). Instead a process view is defended that examines how creativity unfolds over time.

This emphasis on individuals’ engagement in (creative) action is not self-evident. It seems to emphasize the general question why individuals do what they do instead of concentrating on creativity as such. Moreover, it runs counter to prevailing views in creativity research, and has been criticized for that by Ford (2000). Its justification depends on the process description it enables. In this respect, the authors mention two levels, group and organization, later rephrased in terms offered by Weick (1995): intrasubjective (or individual), intersubjective, and collective level of analysis. The group level is discussed in the context of ‘complex, creative projects taken on by large organizations’ that require the concerted engagement of many individuals because skills from multiple bases of expertise are required. No ‘typical’ group level creative behaviors are described. Instead, Drazin et al. (1999: 291) suggest that individuals and groups participate in creative processes in an iterative fashion: “Individuals develop ideas, present them to the group, learn from the group, work out issues in solitude, and then return to the group to further modify and enhance their ideas.”

Added to this picture is the assumption “that individuals act homogeneously within groups as they engage in creative behavior” (op. cit.), which is difficult to understand since ‘homogeneously’ suggests that the members of a group behave identically, to the effect that it is unnecessary to include individual level variables in an analysis of team level creative performance (see Kratzer et al. 2006). It is unclear how this assumption relates to Drazin et al.’s (1999: 301) defense of the assumption of partial inclusiveness – which “suggests that individuals are subject to influence from a multiplicity of groups in which they hold membership (e.g. occupational, organizational, or task)” – at the expense of the assumption of total inclusiveness

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that is usually made. Accordingly, the authors recommend choosing a research context that is “expansive enough to allow a full exploration of multiple and different levels of analysis” (Drazin et al. 1999: 287).

The theory proposed by Drazin et al. (1999) can be viewed as a useful starting point for the study of creativity in organizations, departing (to our knowledge) more than any other from a focus on individuals as the ‘natural bearers’ of creativity. The notion of partial inclusiveness helps to view individuals as participating in several groups, or ‘parts of organizational life’, that an individual may find difficult to reconcile. The way ‘levels’ are treated departs from traditional views of organization in which ‘levels’ or ‘echelons’ are assumed to be fixed, and also departs from traditional, methodology-oriented multi-level analysis which, basically, seeks to ascertain that “effects are not inadvertently collapsed to a single level or otherwise misinterpreted as occurring at the wrong level” in cases that “variables at one level (e.g. the department) affect relations among variables at other levels (e.g. individual employees)” (Craig 2004). However, some additions to the theory are useful. We will indicate (1) further possibilities of group-level creativity, (2) further elaboration of Drazin et al.’s dynamic view of levels, and a more balanced view on the nature of levels, (3) attention for reception (or selection processes), and the implications of the resulting process perspective for the notion of ‘idea’.

(1) While Drazin et al. (1999) attempt to disclose the role of the group, the organization, or some intermediate level, in the end they resort to the view that it are individuals who “work out issues in solitude, and then return to the group” (Drazin et al. 1999: 291). Thus, forms of creative behavior may go unnoticed that are basically interactive or collective: (a) Knowledge complementarity is involved in the example of R&D teams which “bring together experts from a variety of knowledge backgrounds with the expectation that, in combination, they will produce more creative thinking and innovation” (Jackson et al. 1995: 207), and is also involved in the notion of ‘distributed knowledge’ (Tsoukas 1996); (b) Heterogeneity of perspectives may help active discussion to develop which can promote innovative ideas (Hackman 1983); (c) Group-level cognitive processes are shaped by many factors, each of which is itself a process with uncertain outcomes, to the effect that it often will be necessary to go back to an earlier stage of development, a process equivalent to Kline and Rosenberg’s (1986) chain-link model of innovation; (d) Processes of ‘groupthink’ (Paulus 1998) and ‘group polarization’ (Zuber et al. 1992), which are commonly viewed as negative phenomena even though they may merely represent a strong version of ‘shared frame of reference’. Moreover, the view is gaining support that invention is a collaborative rather than an individual achievement (Levine & Moreland 2004).

Except in the case of complementary knowledge, the process of ‘joint creation’ remains to be explained. In this respect, Dankbaar and Vissers (2005) propose ‘a proper lack of understanding’ as a mechanism that originates from differences of perspective that exist between individuals. Such differences stem from different

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experiences (past and present) of individuals – that also underlie Drazin et al.’s concept of partial inclusiveness. These differences will lead to misunderstandings which, in interaction, can be a subject of ‘repair’ attempts. As the interaction continues, views may emerge that none of the interacting individuals would have been able to anticipate. A new view (or idea) has been created.

(2) Researchers engaged in management and organization studies tend to ‘know’ in advance which levels can be observed in an organization. Following House et al. (1995), Drazin et al. suggest a dynamic view according to which organizational levels are emergent rather than fixed. These emergent levels are not necessarily the same as ‘formal levels’. At any level, composition issues can be examined (instead of assuming homogeneity) according to models described by Klein et al. (2001). Moreover, levels are not necessarily formally recognized; they may be informal ‘communities of practice’ – that have been argued to function well only in the absence of formal recognition (Thompson 2005). The connections between these levels, and between different groups at a given level, can be explored using the notion of partial inclusion (or inclusiveness) (Vissers 1994).

Drazin et al. (1999) tend to describe the ‘group’ level in terms of a shared frame of reference, and they tend to describe the organizational level as a negotiated order, that is, a collection of more or less disjoint groups that collaborate on the fragile basis of temporary agreement (Strauss et al. 1963). It is not necessary to make such a sharp distinction. As observed by Drazin et al. (1999: 289), issues of identity are not dealt with the same way in all groups. Phrased differently, groups are not necessarily in harmony. Likewise, organizations are both arenas and sources of identity. Therefore, level characteristics (and their implications for creative processes) should be a subject of inquiry, rather than assumption.

(3) Part of such an inquiry of level characteristics may be the judgments that are made in response to ‘creativity offerings’, and the influence of these judgments on ongoing processes in which creative products may take shape. If judgment as a subject of interest in the context of creativity research, as stressed by Kasof (1995), Ford (1996), Csikszentmihalyi (1999), or Elsbach and Kramer (2003), is added to Drazin et al.’s theory, that may strengthen its capacity to account for organizational processes.

Applying such a process theory to ‘ideas’ is highly relevant for understanding organizational creativity. It may serve to recognize the organizational context in which ideas are assessed and refined, often (we presume) as an ongoing process. This type of analysis may help to disclose the processes that link ideas to great ideas or, for that matter, link small c creativity to Big C creativity. Such processes are social, definitely.

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