How stable is the creative self-concept? A latent state-trait analysis.

Zandi, Nima; Karwowski, Maciej; Forthmann, Boris; Holling, Heinz

doi:10.1037/aca0000521

Cited by 7 publications

(3 citation statements)

References 65 publications

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“…One crucial characteristic is a strong learning-goal orientation (hereafter, "learning orientation"; Hirst et al, 2009). Learning orientation is rooted in the achievement motivation literature, which describes how individuals approach, interpret, and respond to achievement situations, and relates to a motivational orientation that places a strong emphasis on the development of skills and mastery of new tasks 2 While a large part of modern research on creativity in accounting and beyond has focused on finding ways to foster creative thinking among employees to achieve creative outcomes (i.e., supporting them in achieving a creative state; e.g., Grabner, 2014;Kachelmeier et al, 2008;Klein & Speckbacher, 2019), the literature equally highlights the importance of selecting and retaining creative employees, who possess "a cognitive style favorable to taking new perspectives on problems, an application of heuristics for the exploration of new cognitive pathways, and a working style conducive to persistent, energetic pursuit of one's work" to boost innovation (i.e., creativity as a trait; Amabile, 1988, p. 131;Amabile & Pillemer, 2012;Zandi et al, 2022;Zhang et al, 2020). (Dweck & Leggett, 1988;Elliott & Dweck, 1988;Miron-Spektor & Beenen, 2015;Nicholls & Dweck, 1979;Payne et al, 2007).…”

Section: The Loss Of Creative Employees In Randdmentioning

confidence: 99%

The role of target difficulty and career tournaments in retaining creative R&D employees

Grabner,

Seiter,

Wabnegg

et al. 2024

Contemporary Accting Res

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We explore the turnover intentions of creative R&D employees and the role of performance management practices in shaping these considerations. Since the success of a firm's R&D efforts hinges on the innovative ideas of its employees, it is crucial to retain particularly creative individuals. At the same time, however, we argue that this is especially difficult because both the higher outside options of creative employees and their specific individual characteristics make them, on average, more likely to leave their company. Most importantly, we suggest that two widely studied performance management design choices (target difficulty and career tournaments) typically used to motivate effort may influence the loss of creative talent. Using survey data from our unique access to R&D employees of a large manufacturing firm and a complementary experiment among business students, we find evidence that creative employees are, on average, more likely to leave their firm. Consistent with creative employees possessing a stronger learning orientation, we also predict and find that this tendency to leave is mitigated by target difficulty (as difficult targets speak to creative individuals’ learning orientation) and exacerbated by the intensity of career tournaments (as they reduce team cohesion and, ultimately, undermine learning opportunities).This article is protected by copyright. All rights reserved.

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Section: The Loss Of Creative Employees In Randdmentioning

confidence: 99%

The role of target difficulty and career tournaments in retaining creative R&D employees

Grabner,

Seiter,

Wabnegg

et al. 2024

Contemporary Accting Res

View full text Add to dashboard Cite

show abstract

“…Thus, CSC is exactly built upon CSE and CPI. Such understanding has been reflected in empirical research that model this construct as a higher-order factor formed by CSE and CPI (Karwowski, 2012; Lebuda et al, 2021; Zandi et al, 2022; Zielińska et al, 2022). We applied this approach (and conceptualization of CSC) in the present study.…”

mentioning

confidence: 99%

“…We applied this approach (and conceptualization of CSC) in the present study. See also Zandi et al (2022) and Zielińska et al (2022a), for the discussion on caveats of using the CSE term for describing general creative confidence.…”

mentioning

confidence: 99%

Self-regulation for creative activity: The same or different across domains?

Zielińska¹,

Forthmann²,

Lebuda³

et al. 2023

Psychology of Aesthetics, Creativity, and the Arts

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“Who” Is the Best Creative Thinking Partner? An Experimental Investigation of Human–Human, Human–Internet, and Human–AI Co‐Creation

Tang,

Hofreiter,

Werner

et al. 2024

Journal of Creative Behavior

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Recent research suggests that working with generative artificial intelligence (AI), such as ChatGPT, can produce more creative outcomes than humans alone. However, does AI retain its creative edge when humans have access to alternative information sources, such as another human or the internet. We explored this question in a between‐group experiment with 202 German participants across four conditions (human–human dyads, human–Internet, and two human–AI groups with basic or specific instructions) and four creativity tasks (two alternate uses tasks, a consequences task, and a problem‐solving task). Results showed that the human–human condition obtained higher creativity scores in the divergent thinking tasks than the remaining groups. No significant between‐group differences were observed in the problem‐solving task. Moreover, interacting in human dyads made people more creatively confident, an effect not observed in the other groups. In addition, we compared human‐rated outcomes with AI‐based automated scoring (Ocsai). Interestingly, notable discrepancies emerged between the AI assessment and the human‐judged results, raising concerns about AI's susceptibility to “elaboration bias.” These findings highlight the benefits of human collaboration for creativity and call for further studies about the reliability and potential biases of AI in evaluating creative performance.

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How stable is the creative self-concept? A latent state-trait analysis.

Cited by 7 publications

References 65 publications

The role of target difficulty and career tournaments in retaining creative R&D employees

The role of target difficulty and career tournaments in retaining creative R&D employees

Self-regulation for creative activity: The same or different across domains?

“Who” Is the Best Creative Thinking Partner? An Experimental Investigation of Human–Human, Human–Internet, and Human–AI Co‐Creation

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