Exploring technostress dynamics in consulting companies in Germany: A mixed-methods approach
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DOIhttp://dx.doi.org/10.21511/ppm.22(2).2024.46
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Article InfoVolume 22 2024, Issue #2, pp. 586-599
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Technostress (TS) has previously been addressed mainly from a broader organizational perspective, leaving more specific salient settings in the background. This paper bridges this gap by exploring TS dynamics in consulting companies in Germany, a setting that was previously little investigated but is highly TS-prone. This study uses an exploratory mixed-methods approach (MMR) with three components: 1) quantitative validation of the TS test-battery, 2) qualitative exploration of workplace TS through employee experiences, and 3) analysis of the relationship between TS experiences and demographics (age, gender, rank). Quantitative data representativeness is achieved through context-specific test-battery validation and a tailored questionnaire. 702 consulting company employees (based in Germany, aged 18-65) of a renowned management consulting firm participated (m = 417, f = 275). Qualitative data representativeness was ensured through in-depth interviews with 15 employees of different ages, genders, and ranks and company affiliations (Accenture, Boston Consulting Group, Deloitte, Ernst & Young, Roland Berger). Quantitative results indicated that female employees and those above 35 experienced higher levels of Techno-Complexity. Female employees experienced higher TS overall, reflected in their higher Techno-Overload, Techno-Invasion, and Techno-Complexity scores. This applied even to female employees who disagreed with the gender-difference tendency. Additional findings indicated that senior-ranking employees experienced more Techno-Overload and Techno-Invasion. Qualitative results highlighted three themes that further shape the psychological profile of TS in the investigated workplace: a) factors influencing TS, b) TS impact on workplace habits, and c) coping strategies. These findings emphasize that understanding the relationship between creators and demographics is crucial for mitigating consulting workplace TS.
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JEL Classification (Paper profile tab)M12, M54, O33
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References48
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Tables14
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Figures1
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- Figure 1. Factor structure of technostress scale (TO, TI, TC)
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- Table 1. Demographic distribution of survey participants (quantitative data)
- Table 2. Participant demographics for semi-structured interviews (qualitative data)
- Table 3. Descriptive statistics of technostress sub-scales
- Table 4. Results of exploratory factor analysis for technostress sub-scales
- Table 5. Correlation matrix of technostress items
- Table 6. Axial coding results – grouping of codes into categories
- Table 7. Major themes characteristic of the consulting domain
- Table 8. ANOVA test of TO, TI, and TC with respect to gender
- Table 9. Independent t-test scores comparing perceptions of higher technostress in women (TO, TI, TC scores): comparing women who think that women experience higher technostress than men and men who think that women experience higher technostress than men
- Table 10. Independent t-test scores comparing perceptions of higher technostress in women (TO, TI, TC scores): comparing women who do not think that women experience higher technostress than men and men who do not think that women experience higher techno
- Table 11. ANOVA test results of technostress indicators (TO, TI, TC) with respect to age
- Table 12. Stepwise regression analyses predicting TO split by gender
- Table 13. Stepwise regression analyses predicting TI split by gender
- Table 14. Stepwise regression analyses predicting TC split by gender
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