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The purpose of this paper is to examine the effects of final delivery solutions on e-shopping usage behaviour by modelling their interaction across residents living in different neighourhoods with availabilities of different facilities, including automated parcel stations (APSs), collection and delivery points (CDPs), and the direct-to-home delivery stations of parcel express firms (PEFs).

The study is based on a survey on e-shopping behaviour and delivery awareness. A mixed structural equation model is used to predict the interactions among availability of final delivery facilities (AFDF), level of satisfaction with delivery services and e-shopping usage after controlling individual socioeconomic attributes and retail environment.

Compared with AFDF, individual socioeconomic attributes are the most influential factors contributing to e-shopping spending and frequency. Improving AFDF has only a slight effect on e-shopping spending, while a larger impact on e-shopping frequency and perceived satisfaction to delivery services is observed. The quantity of PEF delivery stations has a relatively large influence on e-shopping usage but the effects of APSs and CDPs are not as strong as expected.

The causality between final delivery solutions and e-shopping behaviour can be further tested by using social experiments or longitudinal data.

All findings will help business and public policy decision makers to derive a balanced and effective deployment of final delivery solutions, which is also referential for other emerging markets similar to China.

This study theoretically contributes to the international literature by examining the heterogeneous effects of final delivery solutions on different aspects of e-shopping engagement.

As an application of self-service technology, automated parcel station (APS) is emerging as a logistics innovation to address the inefficiency and delivery failure in conventional home delivery. However, the long-term viability of APS depends on the consumers’ acceptance of such concept. In response, the purpose of this paper is to conduct a behavioural study on consumers’ adoption of self-collection service via APS.

By synthesising theoretical insights from the innovation diffusion literature and attitude theories, a conceptual model is developed and empirically validated. Perceived characteristics of APS are present to directly influence the consumers’ adoption intention, or indirectly through attitude. A total of 170 valid responses are collected from a survey conducted in Singapore and the data are analysed using structural equation modelling.

Consumers’ favourable attitude and perceived relative advantage of APS directly lead to stronger adoption intention. On the contrary, consumers’ perceptions on compatibility and trialability and on complexity indirectly influence their adoption intention via attitude, in a positive and in a negative way, respectively. Additionally, attitude is found to be the most influential factor contributing to consumers’ adoption intention.

The scope of this paper is limited to e-consumers’ initial adoption decision. Future research should examine the consumers’ adoption behaviour further down the innovation adoption process, such as continuance and commitment.

This research conceptualises and validates the consumers’ adoption behaviour of APS from a synthesised view of innovation diffusion and attitude theories, theoretically and empirically contributing to the field of study on logistics innovations from the consumers’ perspective.

E-commerce businesses have been undergoing rapid development for the last five years in the United States and for the past two years in Europe. This sustained growth illustrates the existence of a demand for this type of service, particularly among the youth. Beyond the startup phase, e-commerce companies are continuing to generate significant losses, which point to organisational defects, the most serious being logistic support to this business. Analysis of the e-commerce issue is delicate, given the haziness of the activity's perimeter. E-commerce startups offer services similar to traditional mail-order, and consumer retailing is not clearly stating its objectives in creating its own e-commerce sites.

Logistics is not an organisational technique that is adapted to the rapid and unpredictable changes that e-commerce is experiencing today. Logistics related problems in e-commerce vary according to the type of commercial activity involved, but they are often considerable and sometimes result from the precipitation with which these activities were set up.

The Elida Gibbs distribution centre at Whitwood has the reputation of being one of the most successful applications so far of data processing systems to warehousing in this country. This article is a slightly edited version of the paper presented by Michael Sweet to the EPoS 82 conference in London in September.

Failed deliveries (i.e. deliveries not accomplished due to the absence of customers) represent a critical issue in B2C (Business-to-consumer) e-commerce last-mile deliveries, implying high costs for e-commerce players and negatively affecting customer satisfaction. A promising option to reduce them would be scheduling deliveries based on the probability to find customers at home. This work proposes a solution based on presence data (gathered through Internet of Things [IoT] devices) to organise the delivery tours, which aims to both minimise the travelled distance and maximise the probability to find customers at home.

The adopted methodology is a multi-method approach, based on interviews with practitioners. A model is developed and applied to Milan (Italy) to compare the performance of the proposed innovative solution with traditional home deliveries (both in terms of cost and delivery success rate).

The proposed solution implies a significant reduction of missed deliveries if compared to the traditional operating mode. Accordingly, even if allocating the customers to time windows based on their availability profiles (APs) entails an increase in the total travel time, the average delivery cost per parcel decreases.

On the academic side, this work proposes and evaluates an innovative last-mile delivery (LMD) solution that exploits new AI (Artificial Intelligence)-based technological trends. On the managerial side, it proposes an efficient and effective novel option for scheduling last-mile deliveries based on the use of smart home devices, which has a significant impact in reducing costs and increasing the service level.

Customer service provision is a growing phenomenon on social media and parcel shipping companies have been among the most prominent adopters. This has coincided with greater interest in the development of analysis techniques for unstructured big data from social media platforms, such as the micro-blogging platform, Twitter. Given the growing use of dedicated customer service accounts on Twitter, the purpose of this paper is to investigate the effectiveness with which parcel shipping companies use the platform.

This paper demonstrates the use of a combination of tools for retrieving, processing and analysing large volumes of customer service-related conversations generated between parcel shipping companies and their customers in Australia, UK and the USA. Extant studies using data from Twitter tend to focus on the contributions of individual entities and are unable to capture the insights provided by a holistic examination of the interactions.

This study identifies the key issues that trigger customer contact with parcel shipping companies on Twitter. It identifies similarities and differences in the approaches that these companies bring to customer engagement and identifies the opportunities for using the medium more effectively.

The development of consumer-centric supply chains and relevant theories require researchers and practitioners to have the ability to include insights from growing quantities of unstructured data gathered from consumer engagement. This study makes a methodological contribution by demonstrating the use of a set of tools to gather insight from a large volume of conversations on a social media platform.

Omni-channel shopping affords consumers a variety of delivery options to receive products based on their preferred times and locations. By considering consumers' contributions (physical, social and attentive efforts) in co-creating delivery services, this study investigates their preferences for parcel delivery.

A scenario-based questionnaire survey is conducted for data collection in Singapore (n = 483). Furthermore, a multinomial logistic regression is performed to assess consumers' choice mode of delivery among five alternatives, that is attended home delivery, unattended home delivery, automated self-collection locker, attended pickup point and click-and-collect.

Compared to attended home delivery, consumers who choose the alternatives are found to be more willing to contribute physical effort but less interested in responding attentively to informational updates. Efforts required for social interactions discourage consumers from choosing attended deliveries, prompting unattended alternatives (e.g. home delivery and self-collection) as more attractive choices. Additionally, socio-demographic factors and product value also influence consumers' preferences.

This study contributes to the literature by integrating the theoretical concept of consumer logistics into omni-channel studies, providing a new approach to examining consumers' channel behaviour. With detailed profiling that links product value and consumers' socio-demographics to their choice mode of delivery, the authors create practical insight into the optimal design of omni-channel distribution systems that best harness consumers' voluntary contributions.

The purpose of this paper is to focus on the carbon intensity of “last mile” deliveries (i.e. deliveries of goods from local depots to the home) and personal shopping trips.

Several last mile scenarios are constructed for the purchase of small, non‐food items, such as books, CDs, clothing, cameras and household items. Official government data, operational data from a large logistics service provider, face‐to‐face and telephone interviews with company managers and realistic assumptions derived from the literature form the basis of the calculations. Allowance has been made for home delivery failures, “browsing” trips to the shops and the return of unwanted goods.

Overall, the research suggests that, while neither home delivery nor conventional shopping has an absolute CO₂ advantage, on average, the home delivery operation is likely to generate less CO₂ than the typical shopping trip. Nevertheless, CO₂ emissions per item for intensive/infrequent shopping trips by bus could match online shopping/home delivery.

The number of items purchased per shopping trip, the choice of travel mode and the willingness to combine shopping with other activities and to group purchases into as few shopping trips or online transactions as possible are shown to be critical factors. Online retailers and home delivery companies could also apply measures (e.g. maximising drop densities and increasing the use of electric vehicles) to enhance the CO₂ efficiency of their logistical operations and gain a clearer environmental advantage.

Both consumers and suppliers need to be made more aware of the environmental implications of their respective purchasing behaviour and distribution methods so that potential CO₂ savings can be made.

The paper offers insights into the carbon footprints of conventional and online retailing from a “last mile” perspective.

Due to increasing supply chain complexity, the supply chain uncertainty has become an imperative issue, which hinders the development of modern logistics and supply chain management. The paper attempts to conceptualize reverse logistics uncertainty from supply chain uncertainty literature and present the types of reverse logistics uncertainty in a triadic model.

The concept of reverse logistics uncertainty is developed based on a triadic model of logistics uncertainty and supply chain uncertainty literature. A desk research is conducted to develop a taxonomy of reverse logistics uncertainty. To better depict the reverse logistics uncertainty, we use case studies to discuss the types of reverse logistics uncertainty in the triadic model.

The study reveals four types of supply chain uncertainties in the reverse logistics. We call them reverse logistics uncertainty. Type-A and Type-B uncertainty are new types of supply chain uncertainty in the reverse logistics.

The types of reverse logistics uncertainty have not been empirically validated in industries. Especially, the two new types including Type-A and Type-B reverse uncertainty need further exploration.

Although reverse logistics has been discussed in the past decades, very few studies have been conducted on the supply chain uncertainty in returns management arena. The paper offers valuable insights to better understand the supply chain uncertainty in the reverse logistics. This also provides suggestions for both managers and researchers to reflect on the reverse logistics uncertainty management and business sustainability.

Currently, it is unclear how omnichannel retailers can create a last mile offer that is both attractive and sustainable from an economic and environmental point of view. The purpose of this paper is to explore to which extent consumers are willing to adopt last mile options that are more sustainable and how these options should be composed to remain attractive.

To this end, the authors surveyed a representative sample of Belgian consumers, using choice-based conjoint experiments, and analysed their preferences structures.

Consumers’ preference goes out to free, next day delivery to an address of choice, on regular office hours during the week. However, when free delivery and return are offered, consumers are willing to collect their orders themselves or wait longer for their orders to arrive.

The research findings are important for retailers that (plan to) operate an omnichannel model. For omnichannel retailers with a dense store network, the results indicate that consumers accept their store network as pick-up and return locations, allowing retailers to create a more efficient and sustainable supply chain in which their online and offline activities can be combined.

The research findings contribute to current literature and practice by combining “planet” and “profit” components of sustainability in last mile transport and applying it in the novel omnichannel environment.