Order Picking and E-Commerce: Introducing Non-Parametric Efficiency Measurement for Sustainable Retail Logistics

Abstract

Order picking is a crucial but labor- and cost-intensive activity in the retail logistics and e-commerce domain. Comprehensive changes are implemented in this field due to new technologies like AI and automation. Nevertheless, human worker’s activities will be required for quite some time in the future. This fosters the necessity of evaluating manual picker-to-part operations. We apply the non-parametric Data Envelopment Analysis (DEA) to evaluate the efficiency of n = 23 order pickers processing 6109 batches with 865,410 stock keeping units (SKUs). We use distance per location, picks per location, as well as volume per SKU as inputs and picks per hour as output. As the convexity axiom of standard DEA models cannot be fully satisfied when using ratio measures with different denominators, we apply the Free Disposal Hull (FDH) approach that does not assume convexity. Validating the efficiency scores with the company’s efficiency assessment, operationalized by premium payments shows a 93% goodness=of-fit for the proposed model. The formulated non-parametric approach and its empirical application are promising ways forward in implementing empirical efficiency measurements for order picking operations within e-commerce operations.

Sustainability and Resilience Revisited: Impact of Information Technology Disruptions on Empirical Retail Logistics Efficiency

“…Taking the results from the presented NDEA analysis as well as the systems dynamics model in Figure 7 towards a comparison with established resilience research, we arrive at the following observations: literature is the interrelation between economic sustainability and resilience as the ability to withstand disruptions with adequate resources [82]. Furthermore, this links to resilience and even growth options in times of crisis due to critical infrastructure being a basic resource in relation to individual corporate capacities for change [83].…”

“…In particular, the link between sustainability and resilience is explored by these authors. Another example of where this paper connects to the existing literature is the interrelation between economic sustainability and resilience as the ability to withstand disruptions with adequate resources [82]. Furthermore, this links to resilience and even growth options in times of crisis due to critical infrastructure being a basic resource in relation to individual corporate capacities for change [83].…”

Empirical evidence on human learning and work characteristics in the transition to automated order picking

“…The main advantage of these methods is that they do not require a priori functional relationships. Following Azadeh et al's (2019) call for more data‐driven techniques (e.g., DEA) to benchmark automated systems, early approaches exist that apply DEA (e.g., Loske & Klumpp, 2020) and FDH (Klumpp & Loske, 2021). However, their explanatory power has not been compared with that of existing parametric models and, from a content‐oriented perspective, is not located within the research gap pointed out in previous sections.…”

In pursuit of humanised order picking planning: methodological review, literature classification and input from practice

“…Data envelopment analysis (DEA) is a fine example of a method that could be invoked for such an evaluation. Its inherent ability to account for different indicators makes DEA an appropriate and widely accepted method to assess the performance of warehouses or their order picking system (De Vries, De Koster, and Stam 2016b;Klumpp and Loske 2021). In addition, the reviewed papers in our sample hardly include feedback links between human conduct and these indicators (e.g.…”