Search results

The purpose of this paper is to identify the components of logistics value and examine their influence on customer satisfaction in e-commerce. This study investigates the moderation effect between those two variables using the overall service level in the different industries of e-commerce.

A total of 592 correctly filled questionnaires from telephone and web interviews (computer-assisted telephone interviews and computer-assisted web interviews) were scrutinized. Hierarchical linear modeling (as a part of a wider group of multilevel modeling studies) was used to verify the dependencies between variables from an organization and industry levels.

The logistics factors indicated and described in the paper differently affect the value for the customer. This value is subjective and dynamic. For this reason, the online seller should develop a system to create a sustainable value proposition. It is plausible due to the possibility of choosing the type of delivery, date of collection and change thereof, as well as that of returning the product. Because of all this, the customer decides on the way of the order execution and creates the value chain.

The developed model is aimed at identifying universal relationships that create the customer satisfaction mechanism for the logistics value. However, this may result in other aspects of customer satisfaction being neglected. The authors are aware that the creation of value by a company in e-commerce must be approached in a systematic manner.

The results obtained and the representativeness of the surveyed sample of companies lead to the formulation of implications for business practice. The conclusions of the research definitely indicate a need to build awareness of logistics value and its influence on customer satisfaction through the service level in the industry. Because of the identified components of the logistics value and industry characteristics, managers of online retailers can better run their businesses, increase customer satisfaction, and thus improve their performance.

It is the first study that concerns e-commerce in individual industries, with particular emphasis on logistics and its impact on customer satisfaction.

The success of last-mile delivery is dependent on consumer acceptance of such services, yet little is known about unattended delivery experience. This paper's purpose is to provide empirically based understanding of customer experience dimensions in unattended home delivery.

Using an engaged scholarship approach, this field study investigated nine households that actively used an unattended delivery service for a period of six to nine months. Empirical data were collected primarily from in-depth interviews.

The study demonstrates that unattended delivery experience is a multidimensional construct that comprises consumers' cognitive, emotional, behavioral, sensorial, physical and social responses to the service. The empirical evidence provides rich descriptions of each customer experience dimension, and the research offers a framework and propositions on unattended delivery experience.

The results guide and support managers in assessing and developing delivery services using a consumer-centric approach to enhance customer experience.

This research is one of the first to address unattended delivery experience by providing a comprehensive, empirically grounded framework. The results provide a foundation for future investigations of last-mile delivery experience dimensions.

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.