Enhancing in-store picking for e-grocery: an empirical-based model

Purpose: This paper identifies, configures and analyses a solution aimed at increasing the efficiency of in-store picking for e-grocers and combining the traditional store-based option with a warehouse-based logic (creating a back area dedicated to the most required online items). Design/methodology/approach: The adopted methodology is a multi-method approach combining analytical modelling and interviews with practitioners. Interviews were performed with managers, whose collaboration allowed the development and application of an empirically-grounded model, aimed to estimate the performances of the proposed picking solution in its different configurations. Various scenarios are modelled and different policies are evaluated. Findings: The proposed solution entails time benefits compared to traditional store-based picking for three main reasons: lower travel time (due to the absence of offline customers), lower retrieval time (tied to the more efficient product allocation in the back) and lower time to manage stock-outs (since there are no missing items in the back). Considering the batching policies, order picking is always outperformed by batch and zone picking, as they allow for the reduction of the average travelled distance per order. Conversely, zone picking is more efficient than batch picking when demand volumes are high. Originality/value: From an academic perspective, this work proposes a picking solution that combines the store-based and warehouse-based logics (traditionally seen as opposite/alternative choices). From a managerial perspective, it may support the definition of the picking process for traditional grocers that are offering – or aim to offer – e-commerce services to their customers

Parcel lockers vs. home delivery: a model to compare last-mile delivery cost in urban and rural areas

Purpose This paper investigates the economic performances of two business-to-consumer (B2C) e-commerce last-mile delivery options -parcel lockers (PLs) and traditional home delivery (HD) in contexts where e-commerce is still at its early stages. It analyses and compares two different implementation contexts, urban and rural areas. Design/methodology/approach This study develops an analytical model that estimates delivery costs for both the PL and HD options. The model is applied to two base cases (representative of urban and rural areas in Italy), and sensitivity analyses are subsequently performed on a set of key variables/parameters (i.e. PL density, PL fill rate and PL annual costs). To support the model development and application, interviews with practitioners (Edwards et al., 2011) were performed. Findings PLs imply lower delivery cost than HD, independently from the implementation area (urban or rural): advantages mainly derive from the higher delivery density and the drastic reduction of failed deliveries. Benefits entailed by PLs are more significant in rural areas due to lower PL investments and annual costs, as well as higher HD costs. Originality/value This paper offers insights to both academics and practitioners. On the academic side, it develops a model to compare the delivery cost of PL and HD, which includes the analysis of urban and rural contexts. This could serve as a platform for developing/informing future analytical/optimisation contributions. On the managerial side, it may support practitioners in making decisions about the implementation of PLs and HD, to benchmark their costs and to identify the main variables and parameters at play

E-grocery logistics: exploring the gap between research and practice

Purpose: This paper investigates the logistics management in the e-grocery sector. It contrasts the key issues faced by practitioners and the topics addressed in the academic literature, to identify potential misalignments between research and practice and propose avenues for future efforts. Design/methodology/approach: This work adopts a twofold methodological approach. From an academic perspective, a systematic literature review (SLR) is performed to define the topics addressed so far by scholars when analysing e-grocery logistics. From a managerial perspective, a Delphi study is accomplished to identify the most significant issues faced by logistics practitioners in the e-grocery context and the associated significance. Findings: The study develops a conceptual framework, identifying and mapping the 9 main logistics challenges for e-grocery along 4 clusters, in the light of a logistics-related revision of the SCOR model: distribution network design (area to be served, infrastructures), order fulfilment process (picking, order storage, consolidation, delivery), logistics-related choices from other domains (product range, stock-out management) and automation. These elements are discussed along three dimensions: criticalities, basic and advanced/automation-based solutions. Finally, the main gaps are identified – in terms of both under-investigated topics (order storage and stock-out management) and investigated topics needing further research (picking and automation) – and research questions and hypotheses are outlined. Originality/value: This paper provides a threefold contribution, revolving around the developed framework. First, it investigates the state of the art about e-grocery logistics, classifying the addressed themes. Second, it explores the main issues e-grocery introduces for logistics practitioners. Third, it contrasts the two outcomes, identifying the misalignment between research and practice, and accordingly, proposing research directions

Combining crowdsourcing and mapping customer behaviour in last-mile deliveries

In the light of the dramatic rise of online sales, last-mile deliveries (i.e., the delivery of products ordered online to the final customer) have been increasingly gaining the attention of both managers and academics. As a matter of fact, they are very critical in terms of effectiveness (as customers demand fast and accurate deliveries), and efficiency (since they imply very high costs). Henceforth, logistics players operating in the B2C e-commerce environment are striving to find and implement innovative solutions, different from the costly traditional by-van home deliveries. Among the options analysed by scholars so far, two promising ones are crowdsourcing logistics (i.e., outsourcing delivery activities to “common” people) and mapping the behaviour of customers (i.e., analysing the probability distribution of the customer presence at home and accordingly scheduling deliveries to minimise the probability of failed deliveries). In this paper, we introduce and study a combination between the two solutions, proposing a variant of the Vehicle Routing Problem, which considers both the Availability Profiles and Occasional Drivers (VRPAPOD). We model the delivery problem as a mixed-integer program and solve it with a branch-and-price algorithm. To analyse the benefit of the combined use of crowdshipping and customers availability profiles (APs), we conduct several experiments in a real context in the city of Milan, randomly extracting 100 customers in a 16 km2 area. The combined solution is compared with two benchmarking models, namely the traditional home delivery (traditional VRP) and the crowdsourcing logistics option (Vehicle Routing Problem with Occasional Drivers (VRPOD)). Results prove that logistics players can achieve important benefits by relying on the crowd and scheduling deliveries according to clients' APs, which become more significant in case of high drivers availability

Delivering parcels through a metro-based underground network: an economic analysis

This work proposes the introduction of an innovative method to deliver parcels within urban areas through a two- echelon logistic network, exploiting underground public transportation and cargo bikes. A model simulating the delivery of parcels through underground public transportation and cargo bikes is developed and applied to the city of Milan. Different scenarios, characterized by a different number of train stations activated and a number of daily orders, are investigated. Exploiting available capacity at subway trains reduces the impact of routing empty vehicles for the public infrastructure provider. Besides, as small, capacitated vehicles, cargo cycles allow having an average higher saturation, with the possibility of running multiple trips within the same day, lowering the impact of non-value adding returns for long-haul vehicles coming from outlying distribution centers. Alongside this, the usage of light vehicles and underground infrastructures help to significantly reduce transportation impacts. Overall, the solution proposed has the potential to radically innovate and improve urban last mile delivery under both economic and environmental perspectives. The present work proposes an innovative solution to deliver parcels, showing that it is sustainable from the logistics service operators' perspective

Truck-based drone delivery system: An economic and environmental assessment

Innovative solutions for last-mile delivery have sparked great interest among consumers and logistics operators. The combination of new technologies with existing ones can lead to new possible last-mile delivery configurations, among which truck-drone joint delivery is one of the most promising. This paper evaluates the environmental and economic sustainability of a last-mile delivery solution involving electric trucks equipped with drones, and it provides a comparison with traditional logistics systems. The comparative life cycle assessment methodology is used to quantify the greenhouse gas emissions per parcel delivered. The total cost of ownership methodology is adopted for the economic analysis. Results suggest that the truck-drone alternative leads to significant emissions reductions, while its cost performance is primarily affected by the drone automation level

Advanced crew procedures development techniques

The development of an operational computer program, the Procedures and Performance Program (PPP), is reported which provides a procedures recording and crew/vehicle performance monitoring capability. The PPP provides real time CRT displays and postrun hardcopy of procedures, difference procedures, performance, performance evaluation, and training script/training status data. During post-run, the program is designed to support evaluation through the reconstruction of displays to any point in time. A permanent record of the simulation exercise can be obtained via hardcopy output of the display data, and via magnetic tape transfer to the Generalized Documentation Processor (GDP). Reference procedures data may be transferred from the GDP to the PPP

Dark, cloud and ghost kitchens: a logistics perspective

In recent years multiple countries have witnessed the dramatic diffusion of the so-called “on-demand food delivery”, i.e., a model based on online platforms offering the delivery of freshly prepared meals from restaurants to the customers’ home. In these ecosystems, novel solutions referred to as “Kitchens for Delivery” are being created, which are aimed to fulfil these orders. Differently from traditional restaurants, these are kitchens dedicated to the preparation of online orders only, with no offline customers. This being the context, the present research has a twofold goal. First, identifying and describing the major different models existing in the field (i.e., Dark, Cloud and Ghost Kitchens). Second, estimating their performances from a logistics perspective, by means of an evaluation of their impact on the on-demand food delivery logistics problem. The implemented approach is multi-method, as it combines: (i) the analysis of (black, grey and white) literature, to understand the state of art and map the main solutions; (ii) a simulation study, to assess the changes implied by introducing Ghost Kitchens into the network in terms of delivery performances; (iii) interviews with practitioners, to validate and interpret the results. The research is expected to have both academic and managerial implications. Considering academia, it sheds light on a field that is under-investigated in literature, proposing a classification of extant models, as well as a model to estimate their logistics implications. Considering industry, it provides an estimation of the impact that implementing Ghost Kitchens could have on the most significant logistics performances

Crew procedures development techniques

The study developed requirements, designed, developed, checked out and demonstrated the Procedures Generation Program (PGP). The PGP is a digital computer program which provides a computerized means of developing flight crew procedures based on crew action in the shuttle procedures simulator. In addition, it provides a real time display of procedures, difference procedures, performance data and performance evaluation data. Reconstruction of displays is possible post-run. Data may be copied, stored on magnetic tape and transferred to the document processor for editing and documentation distribution

The RainBO Platform for Enhancing Urban Resilience to Floods: An Ecient Tool for Planning and Emergency Phases

Many urban areas face an increasing flood risk, which includes the risk of flash floods. Increasing extreme precipitation events will likely lead to greater human and economic losses unless reliable and efficient early warning systems (EWS) along with other adaptation actions are put in place in urban areas. The challenge is in the integration and analysis in time and space of the environmental, meteorological, and territorial data from multiple sources needed to build up EWS able to provide efficient contribution to increase the resilience of vulnerable and exposed urban communities to flooding. Efficient EWS contribute to the preparedness phase of the disaster cycle but could also be relevant in the planning of the emergency phase. The RainBO Life project addressed this matter, focusing on the improvement of knowledge, methods, and tools for the monitoring and forecast of extreme precipitation events and the assessment of the associated flood risk for small and medium watercourses in urban areas. To put this into practice, RainBO developed a webGIS platform, which contributes to the “planning” of the management of river flood events through the use of detailed data and flood risk/vulnerability maps, and the “event management” with real-time monitoring/forecast of the events through the collection of observed data from real sensors, estimated/forecasted data from hydrologic models as well as qualitative data collected through a crowdsourcing app