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

Service company's adaptation of supply chain to cope with volatile oil and gas market

The oil and gas market has great significance across the globe, but the unpredictability in this industry is a huge challenge that affects all the supply chains in this market. These conditions contribute to a competitive and diverse market where service firms struggle to keep productivity in order to lower costs and boost operating performance. This paper gathers data on the oilfield service industry and explore existing literature on service supply chain agility to discover empirically the application of strategies that can be implemented within the sector. The major difficulties and risks faced during an oil crisis were identified through analyses on the performance of the leading global service provider (Schlumberger). Global mobility and supplier related challenges were found to be the main factors that harm the company's capacity to deal with market fluctuations. And the constructive tactics developed to achieve a strategic edge over competition have been used as the foundation of this study. Through executives’ interview, internal documentation research and relevant literature review it was discovered that agility in Schlumberger was attained by establishing supply chain visibility and the development of flexible policies and processes. By leveraging internal capabilities and digital solutions to enhance the procurement activities and overcome the looming risks it´s possible to successfully operate in complex market. A recommendation framework was presented as supply chain managers’ benchmarking scheme. This framework highlighted approaches that can be taken in terms of suppliers, internal capabilities and customers as a way to contribute to greater supply chain agility