Heuristic Transfer in the Relationship Between Leadership and Employee Creativity

An Illustration of Leader Heuristic Transfer

In 1984, billionaire investor Warren Buffett publicly debated Michael Jensen, professor at the University of Rochester. Jensen, and three Nobel Laureates, all believed Buffet’s wildly successful record of selecting investments was simply a “three sigma event”—a statistical aberration of chance. However, Price and Kelly (2004) subsequently showed that Buffet’s abilities likely go beyond “luck of the draw.” They estimated the probability of Buffet’s record as the result of blind chance to be one in 100 billion. Buffet’s response to Jensen was equally illuminating. Buffet pointed out that eight other successful investors were beneficiaries of the same set of insights. All nine had been students or protégés of Benjamin Graham, the Columbia professor of finance. Although each of these individuals was intelligent, educated, and considered Graham an inspiration, they specifically credited Graham’s cognitive “framework” and “insights” as critical to their success in determining optimal investments in a complex landscape. Long after exposure to Graham, they used his heuristics to create success in separate firms, via distinct investments, over different periods of time.

Heuristics

So, what is an example of an actual heuristic? One such rule of thumb ascribed to Benjamin Graham succinctly states that the stock market is a “voting mechanism” in the short term, and a “weighing mechanism” over the long term (Dodd & Graham, 1934). Although brief and nontechnical, Graham’s followers indicated that this heuristic served as a guideline for applying Graham’s value investing strategy to their investment decisions. In essence, it indicates that short-term data-points, news stories, expectations of company earnings, and other variables should be considered through a different “lens” than evidence provided by their longer term counterparts. Stated another way, the classification of information as subjective in nature (polling) rather than as an objective estimate of a company’s stock value (weighing) could be expected to have implications on investment decisions using that information.

Bingham, Eisenhardt, and Furr (2007) empirically demonstrated the processes and effects of other specific heuristics. They designated heuristics by the ability to focus attention, save time, be flexible, and limit errors. Bingham et al. proposed that heuristics are rough plans for how one should act in future situations, which decreases the time, resources, and mistakes inherent in trial and error (Eysenck & Keane, 1995). In a study of entrepreneurial firms’ internationalization strategy, they gathered interview data to review elements associated with selection, procedural, temporal, and priority heuristics. Selection heuristics, for example, were informal guidelines for determining which countries the firm would enter (one firm focused on English-speaking countries), and which customers to target (one firm focused on large original device manufacturers). Temporal heuristics involved consistencies regarding elements such as the pace or sequence by which a firm internationalized. Their study indicated that the increased presence of these heuristic “tools” had a positive relationship with internationalization performance which in turn was more significant than firm experience alone.

Hargadon and Fanelli (2002) studied the ongoing interaction of empirical and latent knowledge: knowledge as action and knowledge as possibility. In fact, they used a “tool” analogy to describe latent knowledge transfer across different situations by creative design consulting firms such as IDEO. In one case study, IDEO was tasked with developing an innovative water bottle for a bicycle company. Engineers focused on a bistable valve design (one that would allow the bottle to stay closed in normal use but open when squeezed) because a designer had used a similar valve for a shampoo bottle years before. As it turns out, the valve idea for the shampoo bottle had itself come from an unrelated project involving the same premise for designing an artificial heart valve. In describing these links, Hargadon and Fanelli (2002) recounted an IDEO designer who said his “diverse experiences made his memory ‘one big pile of tools’” and while “each industry has its own set of tools, I only remember the tools, not where they came from” (p. 298).

These examples suggest support for heuristics in facilitating various outcomes, including investment performance, international firm growth, and product design. Though these and other outcomes may or may not involve creativity, heuristic “tools” have been an important focus of creativity research for many years. Gordon (1961) wrote about a process for making the familiar strange, and vice versa, to develop new perspectives. Thomas Edison famously said creativity is “one percent inspiration and 99 percent perspiration” (Hargadon, 2008). Simonton (1999) proposed that new variations were not necessarily serendipitous. They could be guided by existence of knowledge elements in new combinations (Sternberg, 1999). Hogarth (1987) discussed four components of causal reasoning relevant to creativity: (a) a causal field which provides the context in which judgments are made, (b) cues-to-causality, imperfect indicators of the presence or absence of causal relations, (c) judgmental strategies for combining the field and cues in the assessment of cause, and (d) the role of alternative explanations. Finally, in their work on developing computer programs, Pirolli and Anderson (1985) found that most students created new programs via analogy. Their success relied on how well they understood why the analogies worked. In all these examples, specific creative applications for unique situations were rooted in less-specific rules of thumb that facilitated their development.

Heuristic Transfer

In the same manner that an individual might develop heuristics as a result of their own experience with different environments and situations, interaction with other individuals may result in the transfer of heuristics as well. Several studies have identified a phenomenon in which employees exposed to each other have an opportunity for unique combinations of knowledge, and that this opportunity is increased in cases where the individuals are diverse in background, expertise, education, and other factors (Burt, 1992; Reagans & Zuckerman, 2001). In their analysis of leadership and creativity, Reiter-Palmon and Illies (2004) suggested that a leader can prompt creative activity in their employees by intentionally establishing groups that are diverse in their makeup or exposing individuals and groups to diverse experiences in an effort to increase knowledge transfer and enhance capabilities. Burke, Fournier, and Prasad’s (2007) study of medical innovations showed that nonstar scientist exposure to highly prolific “star” scientists resulted in higher subsequent rates of production by the nonstar scientists.

These examples suggest evidence that mixing personnel according to experiences and across projects should produce novel combinations commensurate with knowledge transfer. Yet they do not clarify whether individuals internalize heuristics from one another or simply apply their respective skills in a collaborative manner. This question has been explored in other aspects of the literature on creativity. Basadur, Graen, and Green (1982) showed that training in divergent thinking, a creativity-related process like homospatial thinking (Rothenberg & Sobel, 1981) involving the active consideration of multiple alternative solutions for a given challenge, improves employee creativity.

Basadur and colleagues also showed that Creative Personality Scale (CPS) training significantly improves skills such as generating original solutions to problems (Basadur, Runco, & Vega, 2000), accuracy in evaluating original ideas (Basadur et al., 2000; Runco & Basadur, 1993), fluency in generating solutions to problems (Runco & Basadur, 1993), and enhanced ideation in problem finding (Basadur et al., 1982). Additionally, Kabanoff and Bottger (1991) tested the extent to which CPS training increased ideational fluency as well as flexibility and originality among MBA students with 5 years of work experience. Kabanoff and Bottger interpreted the training effects in the following way: “The main difference between trained and untrained persons is the formers’ willingness and capacity to defer judgment and not to exclude apparently strange, but original and potentially valuable ideas” (p. 243).

Leader Heuristic Transfer and Creativity

In summary, evidence suggests that individuals garner and use their own heuristics to aid in creative production. It is also suggested that tools used or demonstrated by one individual may be adopted by another individual, even if used in a different manner or for different challenges from the first. So, how might leadership factor into the transfer of heuristics? Leaders can shape and articulate the means and goals by which employees assess and engage problems, situations, perspectives, and solutions (e.g., Bono & Judge, 2003; Burns, 1978; Foldy, Goldman, & Ospina, 2008; Podsakoff, Bommer, Podsakoff, & MacKenzie, 2006). Research indicates that leader behaviors and attributes also have an impact on everything from employee turnover (Ferris, 1985), to satisfaction (Judge & Piccolo, 2004), productivity (Tepper, Duffy, Henle, & Lambert, 2006), deviance (Mayer, Kuenzi, Greenbaum, Bardes, & Salvador, 2009), organizational citizenship behavior (Organ, 1988) and, of course, creativity. It could be expected, then, that a leader’s unique experiences embodied in their own heuristics may also affect employees. In fact, it is typical for leaders to have higher levels of expertise (Borgatti & Cross, 2003) and status (Sine, Shane, & Di Gregorio, 2003) than their employees, both of which are believed to predict knowledge transfer across individuals.

The theory developed in this article is built on the premise that the transfer of heuristics found to be useful for one person in one set of circumstances assists another person in new and yet unanticipated situations. Specifically, the theory states that a leader high in LHT enhances the cognitive framework (Baron & Ensley, 2006), the capabilities, of employees. The result is employee production that is novel and useful (i.e., creative). As such, the following hypothesis was tested:

Leader Heuristic Transfer as a Distinct Leadership Construct

To fully depict LHT, it is important to clarify its distinctions from existing leadership constructs that influence creativity. LMX (Scott & Bruce, 1994) is described as a function of close leader–employee relations that are expected to result in employee autonomy and feelings of support which, subsequently, allows the employee the freedom and comfort to try new ideas. Benevolent leadership (Niu et al., 2009) and servant leadership (Neubert et al., 2008) involve individualized consideration of the follower that, similar to LMX, is expected to prompt consideration of ideas outside organizational norms. These constructs, and the extant creativity-related leadership constructs in the literature, differ from LHT in that they focus on enhancing intrinsic motivation (e.g., leader inspirational motivation: Hirst, van Dick, & van Knippenberg, 2009; leader encouragement of creativity: Scott & Bruce, 1994; participative/directive leadership: Somech, 2006; leader promotion focus: Wu, McMullen, Neubert, & Yi, 2008; empowering leadership: Zhang & Bartol, 2010; supervisor developmental feedback: Zhou, 2003). Alternatively, LHT likely improves creativity primarily by arming employees with greater skills for pattern recognition, discovery, and problem solving.

To be sure, a leader such as Benjamin Graham might have ranked high in LHT, and high also in LMX, benevolence, or other leadership behaviors and attributes. In contrast, high LHT might also be illustrated by an exemplary, but gruff drill sergeant; a brilliant, but absent-minded professor; or an outstanding, but narcissistic chief executive officer. Each might lack elements critical to inspirational or motivational leadership constructs, yet still be exceptional examples of leadership in terms of outcomes such as employee creativity. These illustrations distinguish LHT from other leadership constructs previously associated with employee creativity. In short, LHT may or may not accompany, but is not focused on emotional or personal support, charisma, idealized image, or inspirational interaction.

The leadership construct conceptually closest to LHT comes from Bass’ Transformational Leadership. Bass states, “Transformational leadership refers to the leader moving the follower beyond immediate self-interests through idealized influence (charisma), inspiration, intellectual stimulation, or individualized consideration” (Bass, 1999, p. 11)

Though this and other depictions of transformational leadership (Bass & Avolio, 1990; Shin & Zhou, 2003) have a central focus on intrinsic motivation, Bycio, Hackett, and Allen (1995) emphasized leaders developing followers and stimulating thinking. This particular emphasis appears to reside in a dimension of transformational leadership called “intellectual stimulation.”

Avolio, Bass, and Jung (1999) described intellectual stimulation as getting followers to question the typical ways of solving problems, and encouraging them to question the methods they use to improve on them. Alternatively, LHT assesses the degree to which employees believe that their supervisor conveys heuristics that assist them in pattern recognition, discovery, and problem solving. Although intellectual stimulation clearly involves the interpersonal encouragement of effort, its attention to problem solving makes intellectual stimulation the closest cousin to LHT. Because LHT directly addresses leader attempts to improve employee abilities, we believe that LHT should have a distinct effect on employee creativity even in the presence of intellectual stimulation. As such, the second hypothesis tested was

As indicated in the reports of admiration and inspiration by the followers of Benjamin Graham, boosts to intrinsic motivation likely accompanied Graham’s transfer of heuristics. At a general level, a leader who takes an interest in the improvement of his or her employees’ well-being or potential (e.g., servant leadership: Greenleaf, 1977; supervisor developmental feedback: Zhou, 2003) could be expected to increase the intrinsic motivation of those employees even if they are not charismatic in doing so. As stated previously, intrinsic motivation is higher the more employees are attracted to and energized by a task itself, rather than working on a task only in exchange for extrinsic outcomes (Deci & Ryan, 1985). Intrinsically motivated employees tend to be cognitively flexible and persevering (McGraw & Fiala, 1982; McGraw & McCullers, 1979). Therefore, they are likely to find alternative means of solving problems, use nontraditional approaches, and be persistent in their efforts. All these behaviors suggest that an intrinsically motivated individual is likely to exhibit a high level of creativity.

Although not intrinsic to LHT, a leader ranking high in LHT might prompt increases in his or her employee’s intrinsic motivation. This would indicate that intrinsic motivation plays a partial role in the relationship between LHT and employee creativity. Thus, the following hypothesis:

Like the other creativity-related leadership constructs described above, transformational leadership is thought to increase employee creativity primarily by increasing employee intrinsic motivation. Indeed, Shin and Zhou (2003) stated that intrinsic motivation “is often considered the mechanism by which situational factors such as leadership contribute to creativity” (p. 704). They found that transformational leadership had a positive relationship with employee creativity, but that this relationship was partially mediated by intrinsic motivation. Given prior theory and empirical evidence, it was hypothesized that

LHT is distinct from intellectual stimulation and other motivation-based leadership constructs in one critical regard. As implied by the term stimulation, motivation-based leadership constructs such as intellectual stimulation influence creativity primarily through increasing employee intrinsic motivation. Instead of intrinsic motivation as the primary theoretical mechanism in prompting creativity, the role of intrinsic motivation between LHT and employee creative performance is likely secondary. Increased intrinsic motivation and its subsequent benefits, from job involvement (Deci, 1975) to further creativity, are appreciated by-products of LHT, but they are not the means to an end. Leader knowledge transfer that enhances the heuristic toolset of employees should directly result in improved ability to be creative and, as a result, be less affected by intrinsic motivation than motivation-based measures such as leader intellectual stimulation. Thus, the following hypothesis was tested:

Scale Development

The initial LHT measure was developed deductively through utilization of a classification schema prior to data collection (Hinkin, 1995). Nuanced heuristics used across a distinct array of industries and occupations would be exceedingly difficult to identify and define for use in a generalizable measure. In contrast, employees can likely recognize a more general difference between leaders providing motivational support and those imparting heuristics that enhance employee capabilities. Based on this assumption, item creation was guided by the definition of the LHT construct (Schwab, 1980), terminology stated in research by Hogarth (1987) and others, and terms gleaned from investors’ depictions of Benjamin Graham’s leadership. Items were revised to avoid technical terms unfamiliar to the general population (e.g., “heuristics”). Items were also revised to use words such as “teach” and “instill” rather than “share” and “help” to avoid a nomological bias toward emotional bonding and instead emphasize objective knowledge transfer. Eleven items were generated for testing.

Research Setting, Sample, and Procedures

Data for this study were collected via a “triad” electronic survey process. Instead of gathering survey responses from one respondent, initial survey respondents also electronically forwarded unique, confidential surveys to their supervisor and a coworker at their place of employment to establish three perspectives on the same subject matter. Data were only used if all three members of each employee–supervisor–coworker triad completed and submitted a survey. Measures within each survey were only used if more than half of each measure’s items had been completed by the participant.

Business school students were offered an opportunity to earn extra credit for a business class if they successfully gathered completed survey triads. Students in the class were e-mailed survey directions and links to electronic surveys to be provided to an employee, that employee’s supervisor, and a coworker. Employees were required to be employed at least 20 hours per week to participate in the survey. For the 750 students to whom these survey items were offered, 460 students registered with the intent to gather data from an employee, supervisor, and coworker. This represented an initial response rate of 61%. At the close of the study period, an identifying code number was used to associate employee–coworker–supervisor surveys with each other. Triads were eliminated if one or more of the three required participants failed to submit a survey, and if data responses were insufficient for analysis. This resulted in 289 complete survey triads in the final sample for a response rate of 39%.

Participants in the sample worked in a wide variety of businesses including aerospace, manufacturing, recycling, government, design and construction, legal, distribution, grocery, hotels, banking, and retail. In terms of occupation, marketing/sales/service and hospitality/ tourism each constituted roughly 20% of the respondents, with management/administration and finance constituting approximately 10% and 9%, respectively. Other areas included education and training, health science, architecture and construction, agriculture, transportation, and information technology. The average age of employees, supervisors, and coworkers was 27, 40, and 30 years old, respectively, while the percentage of males was 55%, 54%, and 42%. The average tenure in the current job for respondents, supervisors, and coworkers was 3 years, 7 years, and 4 years, respectively. All participant categories reflected a Caucasian majority of 59% to 66%, followed by a mix of minority respondents of Hispanic/Latino (16% to 18%), African American (5% to 8%), Asian American (5% to 9%), and other ethnicities. The percentage of participants working full-time was 48%, 97%, and 61%, respectively.

Measures

Unless indicated otherwise, the scales used a 7-point Likert-type scale, from 1 = strongly disagree to 7 = strongly agree. To avoid measurement error resulting from same source response bias (Podsakoff & Organ, 1986), ratings of perceptions of leadership and job characteristics used coworker responses, ratings pertaining to personal measures used employee responses, and ratings pertaining to employee creativity used supervisor responses.