ARCHETYPES OF DIGITAL BUSINESS MODELS IN LOGISTICS START-UPS

Our work develops an archetypical representation of current digital business models of Start-Ups in the logistics sector. In order to achieve our goal, we analyze the business models of 125 Start-Ups. We draw our sample from the Start-Up database AngelList and focus on platform-driven businesses. We chose Start-Ups as they often are at the forefront of innovation and thus have a high likelihood of operating digital business models. Following well-established methodological guidelines, we construct a taxonomy of digital business models in multiple iterations. We employ different algorithms for cluster analysis to find and generate clusters based on commonalities between the business models across the dimensions and characteristics of the taxonomy. Ultimately, we use the dominant features of the emerging patterns within the clusters to derive archetypes

What constitutes a machine-learning-driven business model? A taxonomy of B2B start-ups with machine learning at their core

Artificial intelligence, specifically machine learning (ML), technologies are powerfully driving business model innovation in organizations against the backdrop of increasing digitalization. The resulting novel business models are profoundly shaped by ML, a technology that brings about unique opportunities and challenges. However, to date, little research examines what exactly constitutes these business models that use ML at their core and how they can be distinguished. Therefore, this study aims to contribute to an increased understanding of the anatomy of ML-driven business models in the business-to-business segment. To this end, we develop a taxonomy that allows researchers and practitioners to differentiate these ML-driven business models according to their characteristics along ten dimensions. Additionally, we derive archetypes of ML-driven business models through a cluster analysis based on the characteristics of 102 start-ups from the database Crunchbase. Our results are cross-industry, providing fertile soil for expansion through future investigations

Dimensions of Digital B2B Platforms in Logistics – A White Spot Analysis

Digital platforms have not only transformed entire B2C market segments but also created new markets benefiting from indirect network effects by providing technological building blocks and infrastructure. Digital platforms and according business models can also be found in the B2B context. Especially, logistics seems to be an adequate application for digital, platform-based business models. The present article focuses on B2B logistics platforms and questions whether principles of B2C platforms can be transferred to the domain of logistics. In order to assess the transferability of B2C platform characteristics, a white spot analysis is conducted along a sample of 54 digital platforms. The goal of the white spot analysis is to provide insights into the characteristics of digital B2B platforms in logistics. Moreover, the analysis provides a basis for the discussion whether B2C platform principles can be adopted in an industrial context

Evaluating Platform Openness in Logistics based on a Taxonomic Analysis

Digital platforms are becoming increasingly important in logistics to enhance business models and ensure competitiveness. As new players enter from the B2C sector, the need to innovate is intensifying for traditional firms. To compensate disadvantages, such as missing platform knowledge or a late entrance, open strategies, e.g., shared governance or open source, can spur platform development and establishment. The resulting open platform ecosystems are a promising approach in entering the platform business for struggling firms. As first initiatives aim to promote open logistics ecosystems, our research objective is to evaluate the current state of openness regarding logistics platforms. We use a taxonomy to identify relevant design elements from a business model’s perspective. Building on the taxonomic analysis, we evaluate relevant openness dimensions to display the current state of openness in logistics platform ecosystems. We conclude by giving an outlook on future research avenues by providing potential research questions

Towards a Taxonomy of API Services in Logistics

Data are a valuable asset for companies in the logistics sector to optimize internally and develop new business models. They can be like a magnifying glass and make previously opaque logistical processes transparent and find previously hidden potentials for optimization. Typical applications are tracking of the transport status, route optimization, or monitoring of pharmaceutical products, or monitoring shocks for fragile cargo along the trade lanes. One way to use data is to tap into publicly or commercially available Application Programming Interfaces. Hereby, logistics service providers can get or provide data automatically via a machine-to-machine interface. However, the landscape of API service providers is vast, unstructured, and intransparent in terms of potential data that companies can leverage. Given their high potential for the logistics industry, the paper proposes a taxonomy of API services in logistics based on the inductive analysis of three API databases

Data-based sustainable business models in the context of Industry 4.0

The concept of Industry 4.0, internationally also often referred to as the Industrial Internet of Things, enables data-driven business models to be implemented in industrial value creation. Further, the concept of Industry 4.0 aims to generate sustainable value in industrial contexts. However, both concepts, Industry 4.0-enabled data-driven business models as well as sustainable business models in Industry 4.0, have scarcely been investigated in extant literature. Hence, this paper aims to contribute to the understanding of research at the intersection of three disciplines: 1) Industry 4.0, 2) data-based business models, and 3) sustainability. For this purpose, relevant concepts and interconnections are drawn based on extant literature in the respective field. Further, this paper presents a research agenda that presents several important aspects of data-based sustainable business models in the context of Industry 4.0. These include, among others, designing data-based value offers that are based on economic as well as social and ecological aspects. Another example are value capture or monetization mechanisms that combine economic and ecologically or socially sustainable perspectives into a potentially multi-sided business model. Finally, the paper presents a perspective on future research and potential challenges in the respective aspects of databased sustainable business models in Industry 4.0

Potentials for AI-Based Data-Driven Business Models in Industry 4.0

Whereas the topics of artificial intelligence (AI) and business model innovation have attracted significant attention in academic research, publications at the intersection of both topics are rather sparse. In response, this paper attempts to interconnect the topics conceptually. In particular, it focuses on AI-driven business models in the context of Industry 4.0, highlighting examples and applications in the industrial context. In industry, first applications of AI applications have been known since several decades, such as in pattern recognition by cameras for failure detection. While applications in process or quality optimization have been improved since then, the clear connection to business models is not always clear. Therefore, this paper attempts to differentiate between examples of AI-driven business models that monetize, e.g., process optimization, or data-driven approaches of entire industrial platforms. In doing so, the present paper presents an overview of categories for AI-driven business model innovation across several industrial examples. As a result, future research can adopt and advance this overview to catego

How Digital Platforms with a Social Purpose Trigger Change towards Sustainable Supply Chains

While digital platforms have been intensively researched, there has been little investigation into their role in sustainable change. Our study focuses on food supply chains and food waste and sustainable challenges. Using data collected from exploratory case studies of digital platforms and traditional actors in the food industry of a Nordic country, we categorized three major sustainable platform types: Alterationist, Redistributor, and Capability Builder. We view these as “Zebras,” a business serving profit and social purpose, and observe their emerging role in the food supply chain. We also identify key dimensions of governance and sustainability impact. With this study, we investigate how digital platforms contribute to sustainable change while also retaining their profit focus

Snackwill: lauching a new brand of healthy snacks in the market

As an in-company project in the scope of an internship at Angry Ventures, the main objective of this project was to support a client on the launch of a brand of healthy snacks delivered to offices through an e-commerce platform. The challenge involved the creation of the brand identity and support on the development of the brand concept. Therefore, different techniques were used inside the action-research methodology together with the client in order to develop the key factors of the brand identity and to outline the business concept in the phase of pre-launch. The development of the brand concept counted with the participation of the start-up acceleration programme AgroUP promoted by the Business Centre Loures Inova at M.A.R.L. – in which different techniques and exercises were applied as part of the programme to support entrepreneurs on validation and definition of business models related to agrifood industry. In the end of the project, the brand was launched in the market through several marketing actions that were implemented as consequence of the conducted research and different techniques applied by the team and the client.Enquanto projeto de empresa no âmbito de um estágio na Angry Ventures, o principal objetivo deste projeto foi apoiar um cliente no lançamento de uma marca de snacks saudáveis entregues a empresas através de uma plataforma de e-commerce. O desafio envolveu a criação da identidade da marca e suporte no desenvolvimento do conceito da marca. Assim, diferentes técnicas foram utilizadas dentro da metodologia pesquisaação em conjunto com o cliente de forma a desenvolver os fatores chave da identidade da marca e desenhar o conceito da mesma na fase de pré-lançamento. O desenvolvimento do conceito da marca contou com a participação do programa de aceleração de start-ups AgroUP promovido pelo Centro de Negócios Loures INOVA situado no M.A.R.L. – em que diferentes técnicas e exercícios foram aplicados como parte do programa de suporte a empreendedores na validação e definição de modelos de negócio relacionados com a indústria agro-alimentar. No fim do projeto, a marca foi lançada no mercado através de diferentes acções de marketing que foram implementadas como consequência da pesquisa desenvolvida e das diferentes técnicas aplicadas pela equipa e pelo cliente