%0 Generic
%A Walczok, Marvin
%C Heidelberg
%D 2024
%F heidok:34808
%R 10.11588/heidok.00034808
%T Friend or foe? How innovative digital technologies affect motivational work characteristics and employees' perceived job insecurity
%U https://archiv.ub.uni-heidelberg.de/volltextserver/34808/
%X The  rising  distribution  of  smart  technology, artificial  intelligence,  robotics,  algorithms,  and automation (STARA) in today’s world of work has the potential to revolutionize what, how, where, and   when humans work by supplementing and substituting work processes. However, it is largely unclear   how these technological changes affect employees. While employees may benefit from the substitution   of tedious and dangerous, they may suffer from STARA creating micro-jobs, polarizing required skill   levels, and evoking job insecurity. Although these rapid technological changes have crucial implications   for  employee  outcomes,  empirical  evidence  of  their  effects  on  employees  is  surprisingly  scarce.   Neglecting to investigate these effects could result in poorly designed, demotivating workplaces of the   future.   Building on the integration of numerous theoretical models and frameworks, this dissertation   examines  how  the  introduction  of  intelligent  assistance  systems  (IASs)  modifies  motivational  work   characteristics  in  modern  assembly.  It  considers  various  scenarios,  such  as  the  assembly  of  simple   products, the assembly of more complex products, and the assembly with intensified product changes.   Applying online experiments with vignette methodology, we experimentally manipulated hypothetical   assembly workstations and instructed participants to rate them regarding motivational work   characteristics.  In  the  first  online  experiment  (N1  =  203  German  and  British  blue-collar  workers)   participants were randomly assigned to one of three conditions (work without vs. work with vs. work   with voluntary use of IASs). Results indicated enhanced feedback from job and information processing   when working with IASs in the assembly of simple products. Thus, they highlight the purely positive   effects of IASs on motivational work characteristics.    Transferring  these  findings  to  the  assembly  of  more  complex  products  in  the  second  online   experiment  (work  without  vs.  work  with  IASs,  N2  =  169  German  workers)  was  limited.  Findings   illuminated that IASs restrict work scheduling, decision-making, and work methods autonomy besides   increasing  feedback  from  job  and  information  processing.  Therefore,  they  indicate  the  contradictory   effects  of IASs  on motivational work characteristics. In a third online experiment  (N3  =  176 German   workers)  we  also  manipulated  the  extent  of  task  rotation  (no  task  rotation  vs.  task  rotation  after  one hour). We fully replicated the results highlighting the contradictory role of IASs, regardless of the extent   of task rotation.  This dissertation further illuminates how employees appraise STARA to threaten their   employment  by  contributing  a  thorough  construct  validation  of  affective  automation-related  job   insecurity, a refinement of the STARA Awareness construct (Brougham & Haar, 2018). Findings from   two cross-sectional studies (N4 = 215, N5 = 224 German employees) and one longitudinal study with a   total  time  lag  of  one  year  (N6  =  233  German  employees)  demonstrated  a  fluctuating  fit  of  the   measurement  model  of  STARA  Awareness  between  independent  samples.  With  the  exclusion  of   cognitive elements and the inclusion of the substitution of core tasks within jobs, we reconceptualized the construct, renamed it to affective automation-related job insecurity, and adapted its measurement.   While affective automation-related job insecurity is weakly associated with cognitive and affective job   insecurity, and negatively with core self-evaluations, it exhibits unique associations with indicators of   technological  change  (positive  relations  with  objective  substitution  potential  and  use  of  STARA).   Moreover,  we  identified  rising  levels  of  affective  automation-related  job  insecurity  over  time  for   employees with moderate use of STARA, and decreasing levels for employees with low and high use   of STARA. Overall,  this  dissertation  provides  vital  empirical  evidence  on  the  beneficial  and  detrimental   effects of STARA on workplaces and employees in today’s world of work. Its findings represent a firm   foundation for fruitful research in digital work design, human-machine interaction, and related fields.   Finally,  considering  these  findings  contributes  to  the  human-centered  development,  implementation,   and use of STARA to maintain a healthy and motivated workforce.