The employee as driver of digital innovation: a qualitative study” The relation of HRM-practices and digital innovative work behavior in manufacturing companies

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This study explored the relation between several HRM-practices and digital innovative work behavior. There has been a long history in the research field of this subject, but since the digital era has changed the way people work and the way companies need to innovate (Stock et al., 2018), these principles might have changed. Several studies indicated that employees are becoming of more importance in innovation processes, especially for digital innovations. Müller and colleagues (2018) highlighted the importance of employees in Industry 4.0 and described it as challenges of employee qualifications and barriers of employee acceptance. The research question of this study was What factors affect digital innovative work behavior of employees through which medium sized manufacturing companies can adhere to Industry 4.0? In order to answer that question, literature was studied to find insights in this issue. Three well-known HRM-perspectives for employee engagement and innovative behavior (AMO, DCS and JDR) were described in order to find out how they can enhance digital innovative work behavior. These perspectives were analyzed through a table describing the core elements and practices coming forth from the perspectives. Three overlapping practices HRM-practices were selected and resulted in an eclectic model. These practices were supposed to have a significant impact on digital innovative work behavior: reward system, job control and job demands. Based on these practices four propositions were proposed and a conceptual mode was drawn. In order to draw conclusions on these propositions, interviews were held at a medium size manufacturing company in the industry for indoor climate systems and energy constructions in buildings. This company was one of the frontrunners regarding the use of cooperating robots and 3D-printers, but was lagging behind with the use digital instruments for administrative tasks on the work floor. Two of the propositions seemed to be confirmed by the results of the interviews: Proposition 1 and Proposition 2. That means that the results of this study indicate that the presence of a reward system has a positive relation with digital innovative work behavior. The opposite counts for high job demands. The results indicate that high job demands has a negative relation with digital innovative work behavior. Regarding proposition 3a, the results were not very clear. Interviewees did not fully agree whether or not they experienced high job control. Yet, they did agree that high job control was necessary for digital innovative work behavior. Regarding proposition 3b, the results of this study indicated that this supposed relation did not exist. Job control did not work as a moderator for the negative effects of job demands. On the contrary, job demands negatively moderated the positive relation of job control with digital innovative work behavior. This resulted in proposition 4: high job demands can moderate the positive effects of high job control on digital innovative work behavior. This result contradicts the implication of the Demand-Control model that predicts that high job demand and high job control combined foster motivation and learning (Dhondt et al., 2014). In this study, the strategy as practice approach was used. Intended practices were compared with the actual experienced impact for work floor employees In the following sections the theoretical and managerial implications will be discussed, finally a reflection of this study will be given.
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