Who fits into the digital workplace? Mapping digital self-efficacy and agility onto psychological traits

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Referenz

Maran, T. K., Liegl, S., Davila, A., Moder, S., Kraus, S., & Mahto, R. V. (2022). Who fits into the digital workplace? Mapping digital self-efficacy and agility onto psychological traits. Technological Forecasting and Social Change, 175(2), 121352. (ABDC_2022: A; ABS_2021: 3; VHB_3: B)

Publikationsart

Beitrag in wissenschaftlicher Fachzeitschrift

Abstract

Today's rapidly changing and volatile markets demand a novel set of skills from organizations and employees that allows them to agilely adapt to and surmount the ever-evolving challenges posed by the ongoing development of digital technologies and changes in market conditions. Previous research conducted on structured workplaces using traditional industrialist paradigms had established an ideal composition of employee traits. However, today's contrasting fast-paced environments may have made those profiles obsolete, prompting the need to identify a profile of personalities and interests that enables organizations to assemble a workforce high in digital self-efficacy, which fundamentally drives organizations’ agility. We proposed and evaluated such a model by conducting two studies at international (Study 1, N = 309) and French (Study 2, N = 1,025) publicly traded organizations. The results indicate the personality dimensions openness to experience and emotional stability and investigative and realistic vocational interests are predispositions for the development of digital self-efficacy. Furthermore, we found corroborative evidence for digital self-efficacy to facilitate workforce agility. These findings offer novel insights into those individual psychological traits that foster an agile workforce and make it well-equipped to face the challenges of rapidly changing digital business environments today and in the future.

Mitarbeiter

Einrichtungen

  • Institut für Entrepreneurship
  • Lehrstuhl für Entrepreneurship und Leadership

DOI

http://dx.doi.org/10.1016/j.techfore.2021.121352