Visualizing Business Ecosystems: Applying a Collaborative Modelling Process in Two Case Studies

Business ecosystems are increasingly gaining relevance in research and practice. Because business ecosystems progressively change, enterprises are interested in analysing their ecosystem, to identify and address such changes. In order to gain a comprehensive picture of the business ecosystem, various stakeholders of the enterprise should be involved in the analysis process. We propose a collaborative approach to model and visualize the business ecosystem and we validate four central roles in the modelling process. The process consists of six steps, namely the definition of the business ecosystem focus, instantiation of the model, data collection, provision of tailored visualizations, collecting feedback and adapting the models, and using the visualization ‘to tell a story’. In this paper, we report case studies of two companies that have instantiated ecosystem models

Understanding the Robot Ecosystem: Don\u27t lose sight of either the trees or the forest

The robot sector in many countries has thrived recently thanks to government supports and innovations in various industries. This study, using the patent database to define the robot sector, reconfigures IO (Input-Output) data to analyze the relationships among various sectors. In particular, we consider the internal description of the robot sector (mesoscopic view—the trees) as well as the relationship between the robot and the non-robot sectors (macroscopic view—the forest), so that we can not only understand robot ecosystems in various dimensions but also develop policy insights. For the sake of systematic analysis of the intra- and inter-sector relations as well as the meso-macro links, this study constructs network models and employs several network measures. Our model and analysis present a good case study to understand the nature of the robot sector in terms of the business ecosystem. This novel approach also contributes to finding out a promising path that leverages the strengths of intra-sector relations and spreads the impact of the robot sector across the macro relations

Understanding the Robot Ecosystem: Don't lose sight of either the trees or the forest

The robot sector in many countries has thrived recently thanks to government supports and innovations in various industries. This study, using the patent database to define the robot sector, reconfigures IO (Input-Output) data to analyze the relationships among various sectors. In particular, we consider the internal description of the robot sector (mesoscopic view—the trees) as well as the relationship between the robot and the non-robot sectors (macroscopic view—the forest), so that we can not only understand robot ecosystems in various dimensions but also develop policy insights. For the sake of systematic analysis of the intra- and inter-sector relations as well as the meso-macro links, this study constructs network models and employs several network measures. Our model and analysis present a good case study to understand the nature of the robot sector in terms of the business ecosystem. This novel approach also contributes to finding out a promising path that leverages the strengths of intra-sector relations and spreads the impact of the robot sector across the macro relations

Charting the Emerging Financial Services Ecosystem of Fintechs and Banks: Six Types of Data-Driven Business Models in the Fintech Sector

The competition and the collaboration of established banks and challenging fintechs are expected to dramatically change the financial services ecosystem. The different types and roles of fintechs as new niche players in the ecosystem are not well understood so far. However, a better understanding of these types and roles is required for incumbent as well as for new actors for defining and aligning their strategies. In this paper, we analyze the business models of 195 fintech companies with a special focus on the role of data. Based on this analysis, we present a structured overview of fintechs’ business areas as well as six data-related business model types. This paper contributes to the research on data-driven business models and business ecosystems by applying and modifying an existing approach for classifying new niche players based on the data dimension of their business models

Ecosystem Intelligence for AI-based Assistant Platforms

Digital assistants like Alexa, Google Assistant, or Siri have seen a large adoption over the past years. Using artificial intelligence (AI) technologies, they provide a vocal interface to physical devices as well as to digital services and have spurred an entire new eco-system. This comprises the big tech companies themselves, but also a strongly growing community of developers that make these functionalities available via digital platforms. At present, only few research is available to understand the structure and the value creation logic of these AI-based assistant platforms and their ecosystem. This research adopts ecosystem intelligence to shed light on their structure and dynamics. It combines existing data collection methods with an automated approach that proves useful in deriving a network-based conceptual model of Amazon's Alexa assistant platform and ecosystem. It shows that skills are a key unit of modularity in this ecosystem, which is linked to other elements such as service, data, and money flows. It also suggests that the topology of the Alexa ecosystem may be described using the criteria reflexivity, symmetry, variance, strength, and centrality of the skill coactivations. Finally, it identifies three ways to create and capture value on AI-based assistant platforms. Surprisingly only a few skills use a transactional business model by selling services and goods but many skills are complementary and provide information, configuration, and control services for other skill provider products and services. These findings provide new insights into the highly relevant ecosystems of AI-based assistant platforms, which might serve enterprises in developing their strategies in these ecosystems. They might also pave the way to a faster, data-driven approach for ecosystem intelligence

The value and structuring role of web APIs in digital innovation ecosystems: the case of the online travel ecosystem

Interfaces play a key role in facilitating the integration of external sources of innovation and structuring ecosystems. They have been conceptualized as design rules that ensure the interoperability of independently produced modules, with important strategic value for lead firms to attract and control access to complementary assets in platform ecosystems. While meaningful, these theorizations do not fully capture the value and structuring role of web APIs in digital innovation ecosystems. We show this with an empirical study of the online travel ecosystem in the 26 years (1995–2021) after the first Online Travel Agencies (OTAs) were launched. Our findings reveal that web APIs foster a dynamic digital innovation ecosystem with a distributed networked structure in which multiple actors design and use them. We provide evidence of an ecosystem where decentralized interfaces enable decentralized governance and where interfaces establish not only cooperative relationships, but also competitive ones. Instead of locking in complementors, web APIs enable the integration of capabilities from multiple organizations for the co-production of services and products, by interfacing their information systems. Web APIs are important sources of value creation and capture, increasingly being used to offer or sell services, constituting important sources of revenue

Four Shades of Customer: How Value Flows in Fintech Ecosystems

The financial sector is undergoing a massive transformation, with new technology-driven players challenging established mechanisms and transforming the sector into a fast-moving market. With the gradual transition from a scale economy to a platform-driven network economy, enterprise networks are gaining strategic importance. Despite the growing interest in fintech’s, research has so far lacked a conceptualization of value creation in fintech ecosystems. Therefore, this research paper aims to analyze key players, value creation activities, and value streams based on the analysis of the business models of payment services, personal financial management, robo-advisory, peer-to-peer lending, trading, and cryptocurrency. We present a holistic value network for the fintech ecosystem based on structured literature review and analysis of 171 fintech companies. We were able to show that fintech platform orchestrates multiple market sides and that customers take four distinct roles at the center of the ecosystem when using fintech services

Visualising Business Data: A Survey

A rapidly increasing number of businesses rely on visualisation solutions for their data management challenges. This demand stems from an industry-wide shift towards data-driven approaches to decision making and problem-solving. However, there is an overwhelming mass of heterogeneous data collected as a result. The analysis of these data become a critical and challenging part of the business process. Employing visual analysis increases data comprehension thus enabling a wider range of users to interpret the underlying behaviour, as opposed to skilled but expensive data analysts. Widening the reach to an audience with a broader range of backgrounds creates new opportunities for decision making, problem-solving, trend identification, and creative thinking. In this survey, we identify trends in business visualisation and visual analytic literature where visualisation is used to address data challenges and identify areas in which industries use visual design to develop their understanding of the business environment. Our novel classification of literature includes the topics of businesses intelligence, business ecosystem, customer-centric. This survey provides a valuable overview and insight into the business visualisation literature with a novel classification that highlights both mature and less developed research directions