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

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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

Smart Retailing: a model to assess the economic sustainability of smart shelf-enabled dynamic pricing

Smart Retailing, a new approach to retail management that leverages digital technologies, is gaining much attention, as it enables innovation and improvements in consumers’ quality of life. However, the potentialities stemming from the application of such technologies are still not fully explored. Investment analyses addressing specific technologies could be useful to fill the academic gaps and guide retailers in their digital transition. This paper aims thus at evaluating the economic sustainability of investment in smart shelves, which are employed to perform dynamic pricing in presence of perishable goods. A model simulating the pricing variation in different scenarios was built and economic and financial analyses were performed to evaluate the sustainability of the investment. Data to feed the model were collected through semi-structured interviews with a smart shelf technology provider and three grocery retailers. The results show that the employment of smart shelves allows retailers to increase their profits. First, they are always able to assign to the product the price which most accurately reflects the customers’ willingness to pay. Second, the costs related to misplacement issues are reduced. This study contributes to the knowledge in this unexplored field by providing a model that simulates the dynamic pricing policy after the introduction of smart shelf technology and evaluates its economical sustainability. It also provides retailers who want to join the digital transformation of the stores with a useful tool to guide their investments

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

Improved antimicrobial activity of nisin-incorporated polymer films by formulation change and addition of food grade chelator

Aims: The following polymers were developed: polyethylene (PE), a PE and polyethylene oxide (70% PE and 30% PEO; PE + PEO) blend, PE and nisin (PE + nisin), PE, nisin, and EDTA (PE + nisin + EDTA), and PE + PEO with nisin (PE + PEO + nisin). Methods and Results: Of the polymers tested, PE and PE + PEO did not exhibit any antimicrobial activity against Brochothrix thermosphacta (BT); however, PE + nisin, PE + nisin + EDTA, and PE + PEO + nisin did. Beef surfaces were experimentally inoculated with 3·50 log10 cfu/cm2 of BT, vacuum packaged with each of the five polymers, and held at 4°C for 21 d. After 3 d at 4°C, BT was reduced \u3e 1·70 log10 by PE + nisin and \u3e 3·50 log10 with PE + nisin + EDTA or PE + PEO + nisin. By 21 d at 4°C, BT was reduced to 0·30 log10 cfu/cm2 when treated with PE + PEO + nisin. Conclusions: It appears that PE + PEO + nisin or PE + nisin + EDTA were more effective for reducing BT, as compared to polymers composed of PE + nisin. Significance and Impact of the Study: Nisin-incorporated polymers may control the growth of undesirable bacteria, thereby extending the shelf life and possibly enhancing the microbial safety of meats

Improved antimicrobial activity of nisin-incorporated polymer films by formulation change and addition of food grade chelator

Aims: The following polymers were developed: polyethylene (PE), a PE and polyethylene oxide (70% PE and 30% PEO; PE + PEO) blend, PE and nisin (PE + nisin), PE, nisin, and EDTA (PE + nisin + EDTA), and PE + PEO with nisin (PE + PEO + nisin). Methods and Results: Of the polymers tested, PE and PE + PEO did not exhibit any antimicrobial activity against Brochothrix thermosphacta (BT); however, PE + nisin, PE + nisin + EDTA, and PE + PEO + nisin did. Beef surfaces were experimentally inoculated with 3·50 log10 cfu/cm2 of BT, vacuum packaged with each of the five polymers, and held at 4°C for 21 d. After 3 d at 4°C, BT was reduced \u3e 1·70 log10 by PE + nisin and \u3e 3·50 log10 with PE + nisin + EDTA or PE + PEO + nisin. By 21 d at 4°C, BT was reduced to 0·30 log10 cfu/cm2 when treated with PE + PEO + nisin. Conclusions: It appears that PE + PEO + nisin or PE + nisin + EDTA were more effective for reducing BT, as compared to polymers composed of PE + nisin. Significance and Impact of the Study: Nisin-incorporated polymers may control the growth of undesirable bacteria, thereby extending the shelf life and possibly enhancing the microbial safety of meats

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

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

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