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Open Access
Article
Publication date: 16 October 2017

Anna Bos-Nehles, Maarten Renkema and Maike Janssen

Although we know that HRM practices can have a huge impact on employees’ innovative work behaviour (IWB), we do not know exactly which practices make the difference and how they…

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Abstract

Purpose

Although we know that HRM practices can have a huge impact on employees’ innovative work behaviour (IWB), we do not know exactly which practices make the difference and how they affect IWB. Thus, the purpose of this paper is to determine the best HRM practices for boosting IWB, to understand the theoretical reasons for this, and to discover mediators and moderators in the relationship between HRM practices and IWB.

Design/methodology/approach

Based on a systematic review of the literature, the authors carried out a content analysis on 27 peer-reviewed journal articles.

Findings

Working with the definitions and items provided in the articles, the authors were able to cluster HRM practices according to the ability-motivation-opportunity framework. The best HRM practices for enhancing IWB are training and development, reward, job security, autonomy, task composition, job demand, and feedback.

Practical implications

The results of this study provide practical information for HRM professionals aiming to develop an HRM system that generates innovative employee behaviours that might help build an innovative climate.

Originality/value

A framework is presented that aggregates the findings and clarifies which HRM practices influence IWB and how these relationships can be explained.

Open Access
Book part
Publication date: 18 July 2022

Marie Molitor and Maarten Renkema

This paper investigates effective human-robot collaboration (HRC) and presents implications for Human Resource Management (HRM). A brief review of current literature on HRM in the…

Abstract

This paper investigates effective human-robot collaboration (HRC) and presents implications for Human Resource Management (HRM). A brief review of current literature on HRM in the smart industry context showed that there is limited research on HRC in hybrid teams and even less on effective management of these teams. This book chapter addresses this issue by investigating factors affecting intention to collaborate with a robot by conducting a vignette study. We hypothesized that six technology acceptance factors, performance expectancy, trust, effort expectancy, social support, organizational support and computer anxiety would significantly affect a users' intention to collaborate with a robot. Furthermore, we hypothesized a moderating effect of a particular HR system, either productivity-based or collaborative. Using a sample of 96 participants, this study tested the effect of the aforementioned factors on a users' intention to collaborate with the robot. Findings show that performance expectancy, organizational support and computer anxiety significantly affect the intention to collaborate with a robot. A significant moderating effect of a particular HR system was not found. Our findings expand the current technology acceptance models in the context of HRC. HRM can support effective HRC by a combination of comprehensive training and education, empowerment and incentives supported by an appropriate HR system.

Details

Smart Industry – Better Management
Type: Book
ISBN: 978-1-80117-715-3

Keywords

Open Access
Book part
Publication date: 18 July 2022

Tanya Bondarouk and Miguel R. Olivas-Luján

Abstract

Details

Smart Industry – Better Management
Type: Book
ISBN: 978-1-80117-715-3

Open Access
Book part
Publication date: 18 July 2022

Abstract

Details

Smart Industry – Better Management
Type: Book
ISBN: 978-1-80117-715-3

Access

Only Open Access

Year

Content type

1 – 4 of 4