E-commerce Delivery Research Articles

Do Smart Loading Zones help reduce traffic congestion? A causal analysis in Pittsburgh

Rising demand for ride-hailing services and e-commerce delivery intensifies competition for urban curbside spaces, leading to uncoordinated travel behavior, increased traffic congestion and social costs. One possible solution to address those issues is Smart Loading Zones (SLZs), equipped with advanced technologies to optimize curbside use. Yet, the real-world impact of SLZs on traffic flow is unclear due to a lack of real-world data and rigorous studies investigating SLZ’s causal effect on traffic speed. With granular speed data and real-world implementations of SLZs from Pittsburgh, PA, this study applies the regression discontinuity design method to rigorously examine the causal impact of SLZs on traffic speed in the downtown network. The results showed that the introduction of SLZs could enhance the traffic speed of the nearby road segments by 4.5%, while controlling for the underlying trend of speed and multiple influential factors such as time, weather, and road characteristics. In addition, SLZs with a short length could statistically improve traffic speed but those with a long length exert no significant effect. These heterogenous effects might be attributed to the weak enforcement at the time of SLZ deployment in Pittsburgh. The results confirmed the overall positive impact of SLZs on improving congestion. However, policies such as effective dimension planning and robust enforcement policies are essential to maximize the benefits of SLZs.

Development of an Online Daily Goods Shopping Demand Model Using Internet-Based Consumption Behavior Survey Data

With the rapid growth of the e-commerce market, how to cater to the demand for last-mile deliveries to households is an important challenge for both policymakers and practitioners. Therefore, the incorporation of e-commerce-driven delivery demand into a freight transportation analysis is required. In this research, we conduct an internet-based survey in Japan to collect data on past in-person and online shopping behaviors and develop a household-based e-commerce demand model that simultaneously estimates e-commerce delivery demand in regard to the total value and order size (or order frequency) using a framework proposed by Sakai et al. Using the estimated model parameters, we conduct a sensitivity analysis using the model to understand the impact of changes in delivery service on e-commerce delivery demand. Focusing on groceries and household goods, we successfully demonstrate the ability of the model framework and obtain insights into the impact of delivery service characteristics on households’ reliance on e-commerce using the model developed based on real-world data.

E-Commerce Delivery Optimization with Bicycle Deliveryman and Dual Autonomous Robots

The rapid growth of e-commerce has led to a surge in package deliveries, particularly during promotional events, resulting in increased workload for deliveryman. To address this challenge, this paper explores traveling salesman problem with bike and two autonomous delivery robots-referred to as 2TSPBR. The robots, each with three different-sized cargo compartments, are responsible for delivering packages of varying sizes. When their inventory is low, they restock from the bicycle’s service points. The Variable Neighborhood Search (VNS) algorithm is employed to generate and optimize delivery routes for the bicycle and robots. The results indicate that the VNS algorithm significantly outperforms the CPLEX solver in terms of computational time, providing rapid convergence to near-optimal solutions. This study demonstrates the efficiency and effectiveness of the proposed VNS algorithm in delivering accurate solutions for the integrated delivery system.

Customer data prediction and analysis in e-commerce using machine learning

Customer churn is a major challenge faced by e-commerce companies, as it leads to loss of revenue and decreased customer loyalty. In recent years, for predicting and reducing client churn machine learning techniques are powerful tools. This research aims to explore the use of machine learning algorithms for predicting customer churn, annual spending, and product on-time delivery in e-commerce. The study first conducted a comprehensive review of the literature on customer churn in machine learning. The literature showed that customer churn has been predicted successfully using a variety of machine learning algorithms, including support vector machine (SVM), random forest, and decision tree in various industries. To address this gap in the literature, the study conducted an empirical analysis of customer churn in e-commerce using machine learning algorithms. The data were then pre-processed and analyzed utilizing machine learning techniques for prediction. According to the study’s findings, machine learning algorithms are effective in predicting customer churn, and product on-time delivery in e-commerce. The best-performing algorithm SVM achieved an accuracy of 83.45% in predicting customer churn and 68.42% for product on-time delivery prediction.

Digitizing the green revolution: E-commerce as a catalyst for clean energy transition in rural China

Currently, numerous rural regions face the dual challenges of energy poverty and environmental pollution, which highlight the urgent need to improve the clean energy consumption structure in these areas. Against the backdrop of digital development, this study employs a series of exogenous treatment effect models to estimate the impact of e-commerce on the transition to clean energy in rural areas and explore its underlying mechanisms using agricultural census big data from China. The results indicate that the adoption of e-commerce can significantly facilitate the transition to clean energy, which remains robust even after addressing endogenous issues. Specifically, villages equipped with an e-commerce delivery station experience a 25% to 41.33% improvement in their natural gas connection rate compared to villages without such facilities. Heterogeneity analysis reveals that the impact of e-commerce on promoting clean energy transition is more pronounced in villages located in the underdeveloped western and highland regions, as well as those with public transportation systems and village secretaries who have education levels below high school. Furthermore, as the likelihood of a village participating in e-commerce decreases, the impact of e-commerce on the clean energy transition strengthens. Lastly, the underlying mechanisms suggest that e-commerce contributes to the transition towards clean energy by strengthening collective action, promoting rural commerce development, and increasing participation in pension insurance. These findings suggest that promoting e-commerce development in rural areas is a crucial strategy for effectively driving energy transition, especially in underdeveloped rural areas.

ONLINE E-COMMERCE STSTEM

The Online E-commerce System (OSMS) serves as a vital tool in the ecommerce sector, ensuring the efficient management and distribution of various products. This abstract presents an overview of the OSMS, highlighting its functionalities, benefits, and potential impact on ecommerce delivery. The purpose of Online E-commerce System is to automate the existing manual system by the help of computerized equipment’s and full-fledged computer software, fulfilling their requirements, so that their valuable data/information can be stored for a longer period with easy accessing and manipulation of the same. The required software and hardware are easily available and easy to work with. Key Features of the system are: 1) Integration of all records of the order.Top of Form 2) Managing the information of the products. 3) Manage the Delivery address, Customer details, Order details. 4) Shows the information and description of the various products.

Assessing the expectations of Generation Z customers towards last-mile delivery in E-commerce: A case study in Ho Chi Minh City

This study focuses on assessing the impact of various factors influencing Generation Z consumers' expectations of last-mile delivery services when purchasing goods on e-commerce platforms within Ho Chi Minh City (HCMC), to improve service quality and propose delivery processes for efficient last-mile delivery. What is new compared to previous studies is the emphasis on the impact of environmental protection policies and green initiatives on the expectations of Gen Z customers. In this study, the authors propose the factor "Environmental Protection Policy" to build a scale to measure customer expectations in last-mile delivery service. A survey involving 435 participants who belong to Gen Z and frequently utilize e-commerce services in HCMC provided the primary data for this analysis. Utilizing quantitative analytical techniques, including Cronbach's alpha reliability test, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and multiple regression analysis, this research tested several hypotheses. The results corroborate that the expectations of Gen Z consumers regarding delivery services on e-commerce platforms in HCMC are significantly shaped by five pivotal factors: Delivery speed, reliability, responsiveness, environmental protection policy, and cost. The study notably highlights cost as the predominant factor exerting the most substantial influence on the expectations concerning last-mile delivery services. This study has made a significant contribution to the body of knowledge that e-commerce platforms and logistics firms may use to raise the bar for delivery services that Gen Z consumers anticipate.

Resource Scheduling Optimization of Fresh Food Delivery Porters Considering Ambient Temperature Variations

In the context of an evolving socio-economic landscape and rising living standards, the online market for fresh products, encompassing fruits, vegetables, meats, dairy, and eggs, has seen substantial growth, necessitating sophisticated logistics for e-commerce home delivery. This study tackles the distinct challenges of fresh product delivery, which demand rigorous adherence to climate conditions and product mix during transport, significantly influencing the operational strategies and scheduling of delivery platforms. To address these challenges, a comprehensive mathematical model was developed to optimize fresh food home delivery scheduling, focusing on reducing spoilage rates and accommodating the dynamic impact of environmental temperature changes. The model posits assumptions of a consistent and ample supply of fresh goods, standard initial quality loss, and efficient porter assignment for multi-category order combinations. It introduces three objective functions, targeting the minimization of fresh food loss, maximization of customer satisfaction, and reduction of distributor costs. The efficacy of the model and its genetic-algorithm-based solution method was assessed through numerical analysis and case studies, illustrating that the model enhances delivery efficiency and service quality across varying temperature conditions. This substantiates the critical role of environmental temperature management in optimizing fresh food delivery, offering a robust framework for advancing logistical operations in the perishable goods sector and ensuring quality and efficiency in fresh food e-commerce delivery.

Priority-based routing: A shortest path algorithm for e-commerce deliveries

Since the COVID-19 pandemic, the popularity of online shopping through social media and e-commerce sites has increased in Bangladesh. Due to different delivery policies of the courier service companies and other unavoidable reasons, products often do not reach the customer on time. This paper proposes an optimized shortest-path algorithm for e-commerce companies to efficiently and quickly deliver products to multiple destinations by considering their priorities. The use of graph theory and the Google Map API provides flexibility and real-time optimization of the shortest-path calculation. The proposed approach introduces two types of demand destinations: normal and priority demanded destinations. The superiority of the proposed algorithm over the conventional delivery system is a 12%–15% increase in the delivery time and a 15%–20% decrease in overall costs. Our proposed algorithm will benefit companies dealing with product delivery systems such as courier product delivery, e-commerce product delivery, and online food delivery.

Green and gamified! An investigation of consumer participation in green last-mile from a gamification affordance perspective

As a recent phenomenon, gamification designs have gained increasing prominence in encouraging consumer participation in green logistics. The primary focus of this study is to investigate how gamification affects customer participation in green last-mile via e-commerce delivery platforms. Adopting an integrated perspective that combines gamification affordances and technology acceptance, this research explores both the utilitarian and hedonic motivations underlying green logistics. A survey questionnaire is designed for data collection (n = 387) and structural equation modelling is applied for data analysis. Our findings suggest gamification affordances of competition, achievement, self-expression, and interactivity as the factors that directly or indirectly influence consumers' intention to engage in green logistics behaviour. This influence is mediated through perceived enjoyment, ease of use, and perceived usefulness. Furthermore, we find that consumers may prioritise social factors such as interactivity affordance over competition and achievement affordances in the gamified green logistics behaviour. These insights not only contribute to a better understanding of consumers' green logistics behaviours but also provide valuable guidance for logistics providers seeking to promote environmentally friendly practices among e-commerce and logistics users.

Hành vi chuyển đổi sử dụng phương tiện vận chuyển xanh của giao hàng chặng cuối trong thương mại điện tử: Tiếp cận từ giá trị tiêu dùng

The study aims to explain switching behavior toward green vehicle usage of last-mile delivery in e-commerce in Vietnam. A research framework is proposed based on perceived values of green vehicles and environmental concerns. The study collects data from 343 shippers who have used fossil fuel-powered vehicles from 04/2023 to 06/2023, and structural equation modeling is applied to examine proposed hypotheses. Results demonstrate that emotional, functional, and social values positively influence environmental concerns and attitude. Epistemic value motivates environmental concerns, whereas this antecedent does not affect attitude. Additionally, environmental concerns and attitude are essential catalysts for fostering switching intention toward green vehicle usage of last-mile delivery. Finally, academic and managerial implications are discussed to assist manufacturers and logistic providers to adopt communication campaigns in order to trigger switching behavior in Vietnam

Drivers and Barriers for Sustainable Last-Mile Delivery Based on E-customers’ Preferences: Examples from Poland and Brazil

The paper aims to identify customers' preferences toward last-mile delivery in e-commerce in Poland and Brazil and diagnoses the drivers and barriers to implement solutions for sustainable last-mile delivery. In order to achieve this aim, a survey was conducted among e-customers in Poland and Brazil, and data were analysed using conjoint analysis. Additionally, an expert panel was established to identify barriers and drivers for implementing last-mile delivery solutions. For Polish customers, price is the most important, while for Brazilian customers, home delivery. The essential barriers inhibiting the implementation of sustainable last-mile delivery solutions are lack of regulation, insufficient green energy sources, the high price of electric vehicles, and fear of their short lifetime. Support from the local government was identified as a primary driver, followed by the organization of free delivery to parcel lockers/pick-up points and education and training of all stakeholders.

Price Discrimination, Backhaul Problems, and Trade Costs: Theory and Evidence from E-commerce Delivery

Price Discrimination, Backhaul Problems, and Trade Costs: Theory and Evidence from E-commerce Delivery

The Impact of Fresh E-commerce Delivery Quality on Customer Satisfaction In China

The Impact of Fresh E-commerce Delivery Quality on Customer Satisfaction In China

Perlindungan dan Tanggung Jawab Hukum Atas Pembatalan Transaksi Jual Beli Melalui Metode Cash On Delivery di E-Commerce

The cash on delivery payment system makes it very easy for the community. However, it cannot be denied that online transaction cancellations occur in the cash on delivery (COD) system and have an impact on the parties involved: sellers, buyers, e-commerce and couriers. The aim of this research is to analyze legal protection and legal responsibility for canceling buying and selling transactions via cash on delivery in e-commerce.As an approach method used a qualitative approach based on empirical research. In this study, primary data were obtained from interviews and questionnaires. For secondary data from a literature survey. The results of this study indicate that the cash on delivery (COD) system can cause anxiety. This requires legal protection efforts to ensure the rights and obligations of the parties in online transactions, as well as more comprehensive education and stronger regulation of online transactions through e-commerce, especially the cash on delivery (COD) method. Preventive measure. e-commerces may have stricter terms of use for cash on delivery (COD) systems. Justice for the parties is realized when the parties are legally protected. Accountability efforts to the aggrieved party, especially the role of the market, must also be maintained. This is very helpful in terms of accountability if there is a problem with paying cash on delivery (COD).

On-demand last-mile distribution network design with omnichannel inventory

E-commerce delivery deadlines are getting increasingly tight, driven by a growing ‘I-want-it-now’ instant gratification mindset of consumers and the desire of online and omnichannel retailers to capitalize on the growth of on-demand e-commerce. On-demand deliveries with delivery deadlines as tight as one or two hours force companies to rethink their last-mile distribution network, since tight delivery deadlines require decentralization of order picking and inventory holding to ensure close proximity to consumers. This fundamentally changes the strategic design process of last-mile distribution networks. We study the impact of incorporating inventory order-up-to level decisions into the strategic design process of last-mile distribution networks with tight delivery deadlines. We develop an approximate inventory model by including an estimate of the cost of late delivery and additional transportation due to local stock-outs in a newsvendor formulation. Such local stock-outs require an order to be delivered from a more distant facility, which may lead to late delivery and additional transportation cost. We integrate our approximate inventory model and a location–allocation mixed-integer program that determines optimal facility locations, associated order-up-to inventory levels, and fleet composition, into a metamodel simulation-based optimization approach. Our numerical analyses demonstrate that pooling the additional online inventory with brick-and-mortar (B&M) inventories leads to cannibalization by the B&M network and higher B&M service levels. However, the pooling benefits to the online network outweigh the cost of inventory cannibalization. Furthermore, we show under which circumstances omnichannel retailers may have an incentive to consolidate online inventory in specific B&M facilities.

Towards more sustainable online consumption: The impact of default and informational nudging on consumers’ choice of delivery mode

The increasing CO2 emissions from e-commerce deliveries present a pressing environmental concern. If half of all consumers decided to have their online order delivered to a pick-up point instead of at home, this could vastly reduce CO2 emissions of e-commerce. This study investigated (a) whether nudging could help consumers shift towards pick-up point delivery as a more sustainable choice, and (b) which type of nudging would be most effective. An RCT was conducted with a representative sample of the Dutch population (N = 1213). In an online store setting, participants selected a product and completed the check-out process – selecting between more and less sustainable delivery options. Their selection had real consequences as the gift would be delivered with the selected delivery method. Four different nudging conditions were contrasted: a default nudge, in which the most sustainable option (i.e., delivery to pick-up point) was selected automatically, and three decision-information nudges, in which CO2 emissions for the delivery options was displayed. The decision-information nudges varied in complexity, from high complexity (emissions in grams of CO2 for each delivery option) to medium (percentage of CO2 reduction for the most sustainable option) and low complexity (a green leaf next to the most sustainable option). Relative to control, the default nudge was the most effective at steering participants towards the most sustainable delivery choice, followed by the medium- and low-informational nudging conditions. In addition, instead of steering them towards the most sustainable delivery option, the high-informational nudge appeared to steer participants away from the two most polluting delivery options – thereby potentially saving more greenhouse gas emissions (GHG) than the other conditions. In sum, this study provides substantial evidence for the use of behavioral strategies in quest towards more sustainable online consumption.

Spatial relationship between sociodemographic and retail access data and e-commerce deliveries: the case of Belo Horizonte (Brazil)

Many negative externalities are associated with home deliveries, the main ecommerce delivery destination. Despite many solutions that address this problem, the lack of understanding of the spatial pattern of urban deliveries makes it challenging to implement these strategies. This paper analyzed the spatial relationship between sociodemographic, retail and e-commerce deliveries in Belo Horizonte (Brazil) by using official data at the neighborhood level (number of retail shops, gender, income, age, race, and household size), and e-commerce deliveries performed by a transportation company. Global Moran's I indicated the spatial dependence of the e-commerce deliveries. Results of a geographically weighted regression model showed a positive spatial effect of retail, women, Asian population, age from 20 to 29 years old, and income. In addition, a negative spatial effect was identified for the size of the household, 18 to 19 years old, and the black population. Furthermore, the estimated coefficients show small spatial variability, indicating homogeneity in the spatial relation. The uniformity of the parameters indicates that alternative strategies can be implemented throughout the territory to reduce e-commerce deliveries.

Operational cost analysis for e-commerce deliveries using agent-based modeling and simulation

The COVID-19 pandemic has highlighted the growth of e-commerce around the world. Especially in developing countries, assisted home delivery (AHD) is the main way for people to receive their goods purchased online. This delivery policy can result in delivery failure when the consumer is not at home and, consequently, in greater externalities that impact all stakeholders in last mile logistics. This paper aims to evaluate the operating costs of delivery lockers (DLs) through agent-based modeling and simulation. A total of 84 scenarios were simulated alternating the DLs usage rate and different delivery attempt policies. The results show that the most impacting system costs are time, external and re-delivery costs. The implementation of DLs and the exclusion of the three-attempt delivery together can reduce these costs and increase net profit by up to 79.1%. Therefore, DLs have economic potential for last mile logistics operations. However, this solution must be accompanied by incentive policies resulting from stakeholder engagement. We hope that this study contributes to a greater understanding of DLs as a sustainable solution for last mile e-commerce deliveries, helping decision makers in urban freight transport.

To Green or Not to Green: The E-Commerce-Delivery Question

In an era in which e-commerce has become an integral facet of our lives, the delivery process has evolved into a vital part of online shopping. As the sole tangible interaction in an otherwise digital undertaking, it forms a decisive aspect of consumers’ e-commerce experience. In the face of the ever-growing prevalence of e-commerce, the ecological footprint left by delivery practices has emerged as a pressing concern. This focus is attributed not only to the environmental externalities resulting from e-commerce delivery but also due to the system’s inherent inefficiencies. As the primary beneficiaries of e-commerce, consumers form a pivotal force in driving sustainable delivery initiatives. This study embarks on an exploration of consumers’ attitudes toward environmentally friendly e-commerce-delivery practices. We aim to investigate whether consumers are willing to bear additional costs for assured green deliveries and identify which sustainable practices they perceive as most effective. A survey was conducted among e-commerce users to show their readiness to incur higher costs for green delivery and accept delayed deliveries if they supported sustainability. However, our findings reveal a conflicting scenario. While consumers display a readiness to opt for green deliveries, the price and speed of delivery emerged as more critical considerations. This study also uncovers significant discrepancies in attitudes towards green delivery based on demographic factors, such as gender and generation. Utilizing multivariate logistic regression, the study outlines the main factors that predict a willingness to pay for guaranteed green delivery. This study’s findings stress the need to balance the drive for speed and cost-effectiveness in e-commerce delivery with the urgency to adopt sustainable practices. It underscores the necessity for e-commerce platforms and logistics partners to take the lead in crafting and implementing innovative green delivery solutions while educating and incentivizing consumers to choose sustainable delivery options.