Data-driven Business Models in Logistics: A Taxonomy of Optimization and Visibility Services

Abstract

The nature of business conduct is changing due to emerging digital technologies and the ever-increasing role of data as a critical resource. Traditional industry branches such as logistics need to adapt accordingly to keep up with change through digitization and to design adequate business models using data. The present article focuses on investigating the anatomy of these data-driven business models in the logistics sector. In order to achieve this goal, the study develops a taxonomy of data-driven business models in logistics. Start-ups serve as the frame of reference, as they are particularly suitable for deriving explicitly novel and vital business models. The study focuses on two particular types of data-driven business models, namely those offering visibility or optimization services in logistics. The goal of the taxonomy is to uncover the structural composition of such business models and to make the results usable as a morphology for innovation.

Designing business model taxonomies – synthesis and guidance from information systems research

“…That notion is supported by Glass and Vessey (1995, p. 65), who state that in taxonomy design, "(…) you must choose between a very specific classification that serves a particular purpose and a more general classification that serves many purposes." Conceptually, one could link general and specific taxonomies to respective business model frameworks, e.g., investigating a general concept such as digital business models (Möller et al, 2019) and, correspondingly, a respective sub-type, such as data-driven business models (Möller et al, 2020).…”

“…A taxonomy with a conceptual frame should subsume various business models that differ in highly general characteristics. Contrarily, a narrow taxonomy should consider a small range of business models and have very detailed, almost atomic characteristics (Möller et al, 2020). In this vein, investigating a domain fully requires broad and narrow conceptual investigation.…”

“…For this reason, corresponding configurations (i.e., taxonomies) should be available for many design situations. To this day, we observe that business model taxonomies emerge from different technologies and in domains as diverse (DaSilva & Trkman, 2014;Zott et al, 2010Zott et al, , 2011, such as mobility (Lembcke et al, 2020;Remane et al, 2016), logistics (Möller et al, 2020), and FinTech (Eickhoff et al, 2017). Thereby, other established industries, like fashion and automotive, lack empirical analysis in the form of taxonomies.…”

Freight-Logistics-as-a-Service – Innovative Geschäftsmodelle für ein datengetriebenes Transportmanagement

“…FreightTech) bekannt, das eine intelligente Nutzung von Daten als Antrieb zur Entwicklung ökosystemorientierter Plattformkonzepte beschreibt (Roland Berger GmbH 2020). Somit agieren die Plattformbetreiber als Datendienstleister für die Akteure in der Transportkette und greifen den notwendigen Bedarf auf Basis des Serviceleistungs-und Bereitstellungsmodells Software-as-a-Service (SaaS) auf (Göpfert and Seeßle 2019;Möller et al 2020). Die Plattformen sind zudem in der Lage, bestehende IT-Systeme wie bspw.…”

A Taxonomy for Data Ecosystems

“…The increasing number of digital technologies makes data a key driver of the digital economy [1]. The development of new methods for data processing and analysis leads to changes in existing businesses as well as to the emergence of new business models [2,3]. Furthermore, in today's networked business world data-driven innovation and creation of economic value is less and less created by a single organization or in traditional value chains [4,5].…”