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

What determines FinTech success? — A taxonomy-based analysis of FinTech success factors

Value creation in the financial services sector has been fundamentally transformed by digitally born financial technology (FinTech) companies. FinTech companies synthesize information systems with financial services. Given its disruptive power, the FinTech phenomenon has received great attention in academic research, practice, and media. Still, limited systematic research provides a structure and holistic view of FinTechs’ success. Aiming to enhance understanding of the factors enabling FinTech success, we classify success factors across extant scientific literature on distinct FinTech business model archetypes. Our analysis reveals that the “cost–benefit dynamic of the innovation,” “technology adoption,” “security, privacy, and transparency,” “user trust,” “user-perceived quality,” and “industry rivalry” are crucial factors for FinTech success and can be seen as “grand challenges” for the FinTech ecosystem. In addition, we validate and discuss our findings with real-world examples from the FinTech industry and two interviews with stakeholders from the FinTech ecosystem. Our study contributes to the knowledge of FinTechs by providing a classification system of success factors for practitioners and researchers

Chasing Cyber Security Unicorns: A Taxonomy-based Analysis of Cyber Security Start-ups’ Business Models

As the number of security incidents increases, a market is emerging for established and new providers of security measures. However, we lack an idea of the business models of cyber security start-ups, which are seen as innovation and security drivers, to protect the economy from existence-threatening incidents. Due to the intangible nature of the cyber threats that security solutions aim to address, previous research on business models cannot be fully transferred. We address this research gap by developing a taxonomy following Nickerson et al. (2013) based on 90 cyber security start-ups and performing a cluster analysis to understand the business activities of cyber security start-ups concerning the protection of critical infrastructures. Our taxonomy will benefit interested decision-makers such as CISOs who want to identify custom-fit cyber security solutions for their organizations. Furthermore, investors and cyber security providers understand the market holistically and can identify innovative product approaches to adopt themselves

Academic production and technological emergence in finance: Bibliometric study on FinTechs

Purpose – This paper aims to study the FinTech enterprises and the management theories related to this subject in a scientific way. Design/methodology/approach – This study is a bibliometric study on FinTech enterprises. Its origin is a survey of 1,749 papers in 6 traditional peer-reviewed academic databases (e.g. Science Direct and Scopus) and in the “gray” literature, published by other agents and not subject to double-blind peer review. In this analysis we use three approaches: academic paper or not; journal main interest, and main purpose of the paper. Findings – The first approach shows 45% of papers without blind review. The second approach shows no concentration on any journal. It represents no concentration on any kind of specific journal. And the third approach shows four kinds of contents in all researched papers: FinTech categorizations; FinTech related to theory of disruptive innovation; FinTech and theories of administration or economy; and finally, FinTech and regulatory and legislative aspects. Originality/value – The findings identified the emergence of new research strands, precedence of studies of “gray” literature to explain the phenomenon, distribution of studies in different fields of knowlePurpose – This paper aims to study the FinTech enterprises and the management theories related to this subject in a scientific way. Design/methodology/approach – This study is a bibliometric study on FinTech enterprises. Its origin is a survey of 1,749 papers in 6 traditional peer-reviewed academic databases (e.g. Science Direct and Scopus) and in the “gray” literature, published by other agents and not subject to double-blind peer review. In this analysis we use three approaches: academic paper or not; journal main interest, and main purpose of the paper. Findings – The first approach shows 45% of papers without blind review. The second approach shows no concentration on any journal. It represents no concentration on any kind of specific journal. And the third approach shows four kinds of contents in all researched papers: FinTech categorizations; FinTech related to theory of disruptive innovation; FinTech and theories of administration or economy; and finally, FinTech and regulatory and legislative aspects. Originality/value – The findings identified the emergence of new research strands, precedence of studies of “gray” literature to explain the phenomenon, distribution of studies in different fields of knowl

Novel approaches for managing platform-based ecosystems

Digitalization challenges existing organizations and industries. The associated advancement changes the way organizations and their customers interact. This has increasingly fostered the emergence of platforms to facilitate such interaction. Online platforms are software or hardware infrastructures that serve as a foundation and facilitate the interaction between multiple parties (e.g., between organizations and users). Organizations create platforms as part of a larger ecosystem. One major challenge concerns the design of platform-based ecosystems so all participants benefit from their participation. The management of associated relationships with other ecosystem participants is consequently a key challenge and demands according foresight. Platform-based ecosystems are subject to research in the field of information systems. Thus, scientific literature addresses many corresponding research questions and provides valuable insights for both research and practice. However, organizations face numerous challenges when engaging in ecosystems. Such challenges are, e.g., to develop new ecosystems, to incentivize participants to participate in the ecosystem, to cooperate with other participants, and to monitor the ecosystem. In this respect, this doctoral thesis provides a brief overview of platform-based ecosystems and the respective participants therein. Further, the thesis addresses four key challenges in the context of platform-based ecosystems, and proposes novel approaches in order to overcome the challenges. The basis for the novel approaches stems from five research papers. The first and second research paper address the challenge of determining design options when developing new ecosystems via blockchain-enabled initial coin offerings. The papers feature a taxonomy and derive predominant archetypes by drawing on real-world cases. The third research paper addresses the challenge of incentivizing users to participate in platform-based ecosystems. The paper proposes an approach to model financial incentives concerning platform adoption. The fourth research paper proposes an approach to analyze organizational cooperation patterns for the purpose of innovation integration. The developed approach incorporates taxonomy development and enables organizations to determine cooperation characteristics to align the cooperation decision with the cooperation objectives. The fifth research paper addresses the challenge of monitoring customer sentiment on online platforms. The proposed design science research artefact includes a detector of negative sentiment such that organizations are able to identify when a negative sentiment develops, and intervene before users spread the sentiment, e.g., through comments. Each research paper answers a stand-alone research question in the realm of platform-based ecosystems and derives a theoretically founded and separately evaluated research artefact. The artefacts draw on underlying, well-established research methods that allow answering the respective problem statements. Since the problem statements are motived in a practical context, this thesis bridges the gap between a practically oriented problem and a theoretically founded solution. As a result, the derived insights contain a contribution for both, research in the field of Information Systems and practice audience, and encourage the engagement of both domains

Demystifying Industrial Internet of Things start-ups – A multi-layer taxonomy

Described as a fundamental paradigm shift by researchers, the Industrial Internet of Things (IIoT) is credited with massive potential. In the context of emerging technologies, such as the IIoT, start-ups occupy a crucial role, as new technologies are often first commercialized by start-ups. Because of the rising importance of IIoT start-ups as drivers of industrial innovation, IIoT solutions demand deepened theoretical insights. As existing classification schemes in the industrial context do not sufficiently account for the ever more critical role of IIoT start-ups, we present a multi-layer taxonomy of IIoT start-up solutions. Building on state-of-the-art literature and a sample of 78 real-world IIoT start-up solutions, the taxonomy comprises ten dimensions and related characteristics structured along the three layers solution, data, and business model. The taxonomy contributes to the descriptive knowledge on the IIoT and enables researchers and practitioners to better understand IIoT start-up solutions

Influencing factors for the digital transformation in the financial services sector

Digital transformation affects almost every area in societies and has consequences for incumbent companies. With qualitative research, we explore the influencing factors for digital transformation in the financial services sector. We use a PEST-model and Porter’s Five Forces as the underlying structure for our analysis. Our interviews and findings show that the financial services sector face the same current challenges, but their impact is perceived higher in the banking than in the insurance sector concerning social factors and bargaining power of buyers. The character of the current development is evolutionary rather than disruptive. Almost all incumbents currently focus on modernizing and consolidating their backend-systems. The aim is to enable them for new customer-oriented services. A primary driver for the digital transformation is the threat of a broader market entry by BigTechs. Our research provides a comprehensive overlook about the influencing factors of digital transformation using statements from experts in the field. © 2020, The Author(s)