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1. Introduction and background
The evolution of customer orders, which are becoming ever more frequent and require smaller amounts of products, has inevitably changed the way their processing is performed by suppliers, who are facing the need to respond very rapidly and flexibly. This trend strongly affects the configuration of picking warehouses and of the activities that have to be carried out within them, with larger pick volumes that have to be satisfied within shorter time windows (De Koster et al., 2007; Bartholdi and Hackman, 2011). One of the priorities for warehouse managers is, therefore, the improvement of picking performance (Battini et al., 2015). Considering that most of the order picking systems are characterised by manual activities performed by human operators, a possible approach for increasing the productivity of order picking systems could focus on pickers’ productivity in terms of reducing the time needed to fulfil an order, and also the reduction of possible errors (Grosse and Glock, 2013; Grosse et al., 2013). In the recent study by Grosse et al. (2015), “Proposition 1” underlines the importance of investigating other objectives besides travel time minimisation in an order picking system. In particular, the need to develop studies that focus on picking error reduction is pointed out including, for example, consideration of the precise possible trade-offs between the cost of investment in paperless information technology and the return on investment from reduced picking errors. Furthermore, according to De Koster and Van Der Poort (1998) and Poon et al. (2009), paperless order picking systems can be a useful strategy to obtain benefits in an order picking warehouse, as validated also in the case studies of some authors in the literature (Berger and Ludwig, 2007; Reif et al., 2010; Yeow and Goomas, 2012). All these studies have concluded that a possible solution that would reduce picking errors and hence improve picking performances is the adoption of paperless picking technologies. According to Frazelle (1988) and Tolliver (1989), for example, it has been estimated that a light-directed picking system with automated data entry can reduce human error by 95 per cent as well as increase productivity by 10 per cent.
A paperless picking system is constituted of a set of devices designed and adopted to facilitate...