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This paper contributes to the theory of the relationship between human resource management (HRM) and innovation at small- to medium-sized enterprises (SMEs) by conducting a conceptual analysis of the question why Germany boasts by far the highest number of “Hidden Champion” SMEs. This is done by case studies from the army and public financial management of aid disbursal in developing countries. Implications for HRM at SMEs are discussed.

Conceptual analysis using case studies.

Contributing towards filling the gap concerning theoretical underpinnings of the link between HRM and innovation, we suggest that interdisciplinary work from relevant organisational case studies indicates that the concept of institutional design to provide motivational incentives may be relevant, especially concerning high performance systems with bundles of HRM practices. Specifically, the fundamental principle of subsidiarity is found to be important.

The research is broadly applicable to organisations of all kinds, as the diverse case studies indicate. We point towards tentative implications for the firms that account for the majority of the work force, namely SMEs, and among them the most successful ones, the so-called “Hidden Champions”.

HR managers can improve motivation, performance and innovation by decentralising decision-making as far as possible, while ensuring the overall organisational goals are well understood and shared, and resources are dedicated to train and educate staff. Additionally, the conception of rank-order competitions complements the institutional design.

Greater productivity and material performance as well as greater job satisfaction via larger autonomy and decision-making power on the local level can be achieved by the application of subsidiarity as key HRM configuration. This can be employed at SMEs, as discussed, but also other organisations. Further, the principle of subsidiarity and the greater emphasis on staff training and education may help reduce inequality.

Our paper contributes towards filling the gap in the literature on the link between HRM and innovation, by identifying the role of subsidiarity. We introduce an interdisciplinary perspective, with contributions from economics and psychology, among others. We also contribute to the history of HRM.

This study investigated the effects of reward system (RS) and job conditions (JC) on employee retention (ER). In particular, this study addressed the mediating effect of employee engagement (EE) on the relationship between RS, JC and ER.

This paper employed descriptive survey approach and the unit of analysis consisted of public hospital nursing staff. Data were collected using questionnaires with a sample of 370 nurse respondents. Structural equation modelling with Smart-Partial Least Squares (PLS) 3.3.8 was used in a statistical analysis.

The results revealed that RS and JC significantly related to ER. The study also showed the direct effect of RS and JC on EE. These findings indicate that (EE) has a partial mediating role in the relationship between RS, JC and ER.

The study offers important policy insights for public nursing stakeholders who seek to increase retention of skills among their nursing staff. The findings are also crucial because they may help the health sector improve their ER strategies, especially in dynamic and competitive business situations where organisations are challenged to retain personnel from a limited skilled workforce.

The findings of this study contribute to the literature on retention of nursing employees by enhancing the understanding of the influences of EE, RS and JC on ER among public hospitals.

Interruptions are prevalent in knowledge work, and their negative consequences have driven research to find ways for interruption management. However, these means almost always leave the responsibility and burden of interruptions with individual knowledge workers. System-level approaches for interruption management, on the other hand, have the potential to reduce the burden on employees. This paper’s objective is to pave way for system-level interruption management by showing that data about factual characteristics of work can be used to identify interrupting situations.

The authors provide a demonstration of using trace data from information and communications technology (ICT)-systems and machine learning to identify interrupting situations. They conduct a “simulation” of automated data collection by asking employees of two companies to provide information concerning situations and interruptions through weekly reports. They obtain information regarding four organizational elements: task, people, technology and structure, and employ classification trees to show that this data can be used to identify situations across which the level of interruptions differs.

The authors show that it is possible to identifying interrupting situations from trace data. During the eight-week observation period in Company A they identified seven and in Company B four different situations each having a different probability of occurrence of interruptions.

The authors extend employee-level interruption management to the system-level by using “task” as a bridging concept. Task is a core concept in both traditional interruption research and Leavitt's 1965 socio-technical model which allows us to connect other organizational elements (people, structure and technology) to interruptions.