Search results

1 – 2 of 2
Per page
102050
Citations:
Loading...
Available. Open Access. Open Access
Article
Publication date: 30 April 2021

Sierdjan Koster and Claudia Brunori

Ongoing automation processes may render a fair share of the existing jobs redundant or change their nature. This begs the question to what extent employees affected invest in…

2672

Abstract

Purpose

Ongoing automation processes may render a fair share of the existing jobs redundant or change their nature. This begs the question to what extent employees affected invest in training in order to strengthen their labour market position in times of uncertainty. Given the different national labour market regimes and institutions, there may be an important geographical dimension to the opportunities to cope with the challenges set by automation. The purpose of this study is to address both issues.

Design/methodology/approach

Using data from the 2016 European labour Force Survey, the authors estimate with logit and multi-level regression analyses how the automation risk of a worker's job is associated with the propensity of following non-formal education/training. The authors allow this relationship to vary across European countries.

Findings

The results show that employees in jobs vulnerable to automation invest relatively little in training. Also, there are significant differences across Europe in both the provision of training in general and the effect of automation on training provision.

Originality/value

While there is quite a lot of research on the structural labour market effects of automation, relatively little is known about the actions that employees take to deal with the uncertainty they are faced with. This article aims to contribute to our understanding of such mechanisms underlying the structural macro-level labour-market dynamics.

Details

International Journal of Manpower, vol. 42 no. 8
Type: Research Article
ISSN: 0143-7720

Keywords

Access Restricted. View access options
Article
Publication date: 12 February 2020

Abla Chaouni Benabdellah, Asmaa Benghabrit and Imane Bouhaddou

In the era of industry 4.0, managing the design is a challenging mission. Within a dynamic environment, several disciplines have adopted the complex adaptive system (CAS…

275

Abstract

Purpose

In the era of industry 4.0, managing the design is a challenging mission. Within a dynamic environment, several disciplines have adopted the complex adaptive system (CAS) perspective. Therefore, this paper aims to explore how we may deepen our understanding of the design process as a CAS. In this respect, the key complexity drivers of the design process are discussed and an organizational decomposition for the simulation of the design process as CAS is conducted.

Design/methodology/approach

The proposed methodology comprises three steps. First, the complexity drivers of the design process are presented and are matched with those of CAS. Second, an analysis of over 111 selected papers is presented to choose the appropriate model for the design process from the CAS theory. Third, the paper provides methodological guidelines to develop an organizational decision support system that supports the complexity of the design process.

Findings

An analysis of the key drivers of design process complexity shows the need to adopt the CAS theory. In addition to that, a comparative analysis between all the organizational methodologies developed in the literature leads the authors to conclude that agent-oriented Software Process for engineering complex System is the appropriate methodology for simulating the design process. In this respect, a system requirements phase of the decision support system is conducted.

Originality/value

The originality of this paper lies in the fact of analysing the complexity of the design process as a CAS. In doing so, all the richness of the CAS theory can be used to meet the challenges of those already existing in the theory of the design.

Details

Journal of Engineering, Design and Technology , vol. 18 no. 6
Type: Research Article
ISSN: 1726-0531

Keywords

1 – 2 of 2
Per page
102050