TITLE: Consumers’ choice preferences for a Data-Driven-Business-Model (DDBM) for last-mile logistics services
AUTHORS: Alexia Irakleous, Maria Lambrou
ABSTRACT: The business environment of e-shopping and parcel delivery services is a dynamic market sector due to emerging technologies and the ever-increasing role of data as a critical resource. E-commerce deliveries in the last-mile of the supply chain involve individuals and not plain postal addresses. The choice process of e-shopping and parcel delivery services, will be quantified using the technique of Stated Preference (SP) Experiments through which respondents will choose the most preferred delivery service, by trading off the different service attributes. To this end, the demand for e-shopping and parcel delivery services will be estimated applying a Nested- Multinomial Logit Model (N-ML) and the results of the econometric analysis will feed the business elements of an innovative Data-Driven Business Model (DDBM) for last-mile logistics services. Following the taxonomy development method of Nickerson et al. (2013) and applying the VISOR framework we analyze business models for Delivery Service Providers (DSPs) who operate in a digital ecosystem. The final taxonomy of DDBM consists of five meta-dimensions, seventeen building blocks, and their associated characteristics depicted as a morphological box. As a last step, the taxonomy developed evaluated by a case study to postal services.
KEYWORDS: Data-Driven-Business Model, last-mile logistics, Nested-Multinomial Logit Model, taxonomy, VISOR framework, postal services
PAGES: 30-40
DOI: