Logistics challenges of e-grocery last-mile delivery: a literature review

In recent years, e-commerce has been growing globally and online markets have undergone a radical transformation during Covid-19 Pandemic. In this context, Food and Grocery sector has expanded exponentially thus leading to a development of last-mile logistics which is the least efficient supply chain activity in terms of economic and environmental impact. At the moment, B2C e-commerce players face multiple challenges due to logistics complexities and efficiency. On the other side, demand complexities rise from Service Level expectations, and consumers’ willingness to pay for logistics services. Food and Grocery e-commerce has three main configurations: the enogastronomic e-commerce, the on-demand food delivery and the e-grocery. Among these, the third one has reported the highest growth during and after the Pandemic. However, beside complexities of e-commerce logistics, the online purchase of grocery products raises new challenges due to product peculiarities, logistics requirements and complexity of orders. The aim of this work is therefore to investigate which are the main problems associated with last-mile delivery for e-grocery and which are the appropriate variables to describe them. In order to achieve this objective, a Systematic Literature Review has been performed to identify key issues addressed by scholars and existing typologies of last- mile delivery problems in this sector. The contribution of this research is threefold: firstly, it analyses the state of the art of last-mile challenges for e- grocery from an academic perspective and proposes a classification. Secondly, the identification of logistics variables associated with identified problems highlights potential threats for E-grocery players. Therefore, this work supports managers to identify challenges in a structured way before planning appropriate countermeasures for the specific context. Thirdly, it identifies opportunities for future research directions

Research on Urban End-Delivery Paths Considering the Consumer\u27s Delivery Time Demand

Delivery time is an increasingly important consideration in consumer behavior, and there are still some problems in the urban logistics and delivery industry in considering matching consumer demand and improving logistics and delivery efficiency to control enterprise costs. In this paper, we will construct an end delivery path model based on consumers\u27 delivery time preference, use ALNS algorithm to analyse the distribution routes of five real communities, and conclude that the total distribution cost increases and then decreases with the increase of the number of consumers who choose value-added services. In this paper, we use scientific methods to calculate and design distribution routes to reduce distribution costs and further satisfy consumer preferences. At the same time, from the perspective of the industry management department, delivery enterprises and the consumers, three main bodies, the next development direction is proposed for different main bodies to promote the high-quality development of urban logistics and delivery market

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

An optimisation approach for the e-grocery order picking and delivery problem

[EN] Traditional supermarket chains that are adopting an omni-channel approach must now carry out the order picking and delivery processes to serve online orders, previously done by the customer. The complexity of the logistics processes has increased, therefore modelling and optimising e-grocery operations becomes definitely important. Since there are few studies modelling order picking and delivery processes, we propose an approach that simultaneously optimises the decision variables of different functions which have traditionally been treated separately. In this study, we present a linear programming model for store-based e-fulfilment strategies with multiple picking locations. The proposed model optimises the allocation of online orders to stores, based on the e-fulfilment costs. As well as minimising the picking and delivery costs, the proposed approach consolidates workloads in order to avoid idle times and reduce the amount of resources required. A weighted sum method is applied to compute the solution, integrating parameters that represent different store features such as the product range, sales mode and physical store activities. The proposed model has been tested on one of the largest grocery sellers, showing that substantial savings can be achieved by reallocating orders to different stores, time windows and delivery vehicles. By focusing on optimising e-fulfilment resources, this approach serves as a guide for traditional grocery sellers to redesign their supply chains and to facilitate decision-making at a managerial level.Funding was provided by Universidade de Vigo.Vazquez-Noguerol, M.; Comesaña-Benavides, J.; Poler, R.; Prado-Prado, JC. (2022). An optimisation approach for the e-grocery order picking and delivery problem. Central European Journal of Operations Research. 30(3):961-990. https://doi.org/10.1007/s10100-020-00710-9S96199030

Differentiated time slot pricing under routing considerations in attended home delivery

In this paper, we study an e-grocer’s tactical problem of differentiated time slot pricing in attended home delivery. The purpose of differentiating delivery prices is to influence customers’ choice behavior concerning the offered time slots, such that cost-effective delivery schedules on an operational level can be expected and overall profit is maximized. We present a mixed-integer linear programming formulation of the problem, in which delivery costs are anticipated by explicitly incorporating routing constraints, and we model customer behavior by a general nonparametric rank-based choice model. Concerning cost anticipation, we also propose a model-based approximation that enables application to real-world problem sizes. In a setup inspired by an industry partner operating in urban areas, we then perform a comprehensive computational study that reveals the value of the model-based approximation as a supporting instrument for an e-grocer’s pricing decisions in practice. In particular, we demonstrate the superiority of the model-based approximation for real-world problem sizes to several benchmark approaches applied in the scientific literature and in practice (e.g., a unit price approach and other standard pricing heuristics). The online appendix is available at https://doi.org/10.1287/trsc.2017.0738 . </jats:p

Business logistics models in omni-channel: a classification framework and empirical analysis

Purpose – Companies are currently moving from multi-channel strategies to offer their customers an omni-channel (OC) experience. So far, OC research has been mainly tackled from a sales-based view, with numerous operational challenges to be fully investigated yet. The purpose of this paper is to investigate how companies set the logistics variables in their OC management strategy and the business logistics models currently most adopted. Design/methodology/approach – A two-step methodology was adopted. First, a systematic combining approach with scientific literature review and case studies allowed to derive a framework for classifying the key logistics variables and the related options. The framework was then used to conduct a qualitative survey targeting 92 Italian companies operating in food manufacturing, food retailing and non-food retailing. Collected data were analysed by means of cluster analysis. Findings – Implementing an OC management strategy requires to set 11 logistics variables belonging to four strategic areas: delivery service, distribution setting, fulfilment strategy and returns management. A broad empirical investigation showed the choices made by companies when setting the logistics variables to implement an OC management strategy. Lastly, four business logistics models, differing in terms of both business sector and OC maturity, were discussed. Originality/value – The proposed framework extends earlier studies by including additional significant logistics variables. The empirical analysis provides new insights on how to re-structure the business logistics model in OC, suggesting channel integration and the coexistence of multiple configurations as main enablers of an OC proposition

Multitrip vehicle routing with delivery options: a data-driven application to the parcel industry

To make the last mile of parcel delivery more efficient, service providers offer an increasing number of modes of delivery as alternatives to the traditional and often cost-intensive home delivery service. Parcel lockers and pickup stations can be utilized to reduce the number of stops and avoid costly detours. To design smart delivery networks, service providers must evaluate different business models. In this context, a multitrip vehicle routing problem with delivery options and location-dependent costs arises. We present a data-driven framework to evaluate alternative delivery strategies, formulate a corresponding model and solve the problem heuristically using adaptive large neighborhood search. By examining large, real-life instances from a major European parcel service, we determine the potential and benefits of different delivery options. Specifically, we show that delivery costs can be mitigated by consolidating orders in pickup stations and illustrate how pricing can be applied to steer customer demand toward profitable, eco-friendly products

Integrated Shift Scheduling and Load Assignment Optimization for Attended Home Delivery

International audienceIn this paper, we study an integrated shift scheduling and load assignment optimization problem for attended home delivery. The proposed approach is divided into two phases, each one corresponding to a different planning level: tactical and operational. In the tactical planning, a daily master plan is generated for each courier. This master plan defines the working shifts, the origin-destination pairs to visit, and the number of client requests to serve. In the operational planning, delivery orders are allocated to couriers in real-time. The stochastic and dynamic nature of client orders is included in the tactical and operational decision levels, respectively. Results on real-world based instances from a delivery company, demonstrate that our approach provides robust tactical solutions that easily accommodate to fluctuations in client orders, preventing additional costs related to the underutilization of couriers and to the use of external couriers to satisfy all delivery requests