Search results

The role of robotization in work design

Robots are increasingly used in a variety of work environments, but surprisingly little attention has been paid to how robots change work. In this comparative case study, we explore how robotization changed the work design of order pickers and order packers in eight logistic warehouses. We found that all warehouses robotized tasks based on technological functionality to increase efficiency, which sometimes created jobs consisting of ‘left-over tasks’. Only two warehouses used a bottom-up approach, where employees were involved in the implementation and quality of work was considered important. Although the other warehouses did not, sometimes their work design still benefitted from robotization. The positive effects we identified are reduced physical and cognitive demands and opportunities for upskilling. Warehouses that lack attention to the quality of work may risk ending up with the negative effects for employees, such as simplification and intensification of work, and reduced autonomy. We propose that understanding the consequences of robots on work design supports HR professionals to help managing this transition by both giving relevant input on a strategic level about the importance of work design and advocating for employees and their involvement.

Methodological quality of front-of-pack labeling studies

This review evaluates the methodological quality of current front-of-pack labeling research and discusses future research challenges. Peer-reviewed articles were identified using a computerized search of the databases PubMed andWeb of Science (ISI) from1990 to February 2011; reference lists fromkey published articleswere used as well. The quality of the 31 included studies was assessed. The results showed that the methodological quality of published front-of-pack labeling research is generally low to mediocre; objective observational data-based consumer studies were of higher quality than consumer studies relying on self-reports. Experimental studies that included a control group were lacking. The review further revealed a lack of a validated methodology to measure the use of front-of-pack labels and the effects of these labels in real-life settings. In conclusion, few methodologically sound front-of-pack labeling studies are presently available. The highest methodological quality and the greatest public health relevance are achieved by measuring the health effects of front-of-pack labels using biomarkers in a longitudinal, randomized, controlled design in a real-life setting.

Understanding Chinese Tourists : Educational pack

The educational Pack contains: a reader, containing the materials for lectures, incl. assignments, director’s statement, a list of further readings, topics for research or papers; The documentary Ni Hao Holland on DVD. This documentary is about authenticity that is created by some and experienced by others in the field of tourism; Slides on a USB stick that relate to the content of the chapters.

Hubs – Waarom het op papier mooi klinkt, maar in de praktijk zelden een groot succes wordt.

A multi-start simheuristic for the stochastic two-dimensional vehicle routing problem

The two-dimensional vehicle routing problem (2L-VRP) is a realistic extension of the classical vehicle routing problem where customers’ demands are composed by sets of non-stackable items. Examples of such problems can be found in many real-life applications, e.g. furniture or industrial machinery transportation. Often, these real-life instances have to deal with uncertainty in many aspects of the problem, such as variable traveling times due to traffic conditions or customers availability. We present a hybrid simheuristic algorithm that combines biased-randomized routing and packing heuristics within a multi-start framework. Monte Carlo simulation is used to deal with uncertainty at different stages of the search process. With the goal of minimizing total expected cost, we use this methodology to solve a set of stochastic instances of the 2L-VRP with unrestricted oriented loading. Our results show that accounting for systems variability during the algorithm search yields more robust solutions with lower expected costs.

Rambutan processing and packing