Philipp Alexander Ebel

Facilitated by AI technology, the phenomenon of cognitive automation extends the scope of deterministic business process automation (BPA) through the probabilistic automation of knowledge and service work. By transforming work systems through cognitive automation, organizations are provided with vast strategic opportunities to gain business value. However, research lacks a unified conceptual lens on cognitive automation, which hinders scientific progress. Thus, based on a Systematic Literature Review, we describe the fundamentals of cognitive automation and provide an integrated conceptualization. We provide an overview of the major BPA approaches such as workflow management, robotic process automation, and Machine Learning-facilitated BPA while emphasizing their complementary relationships. Furthermore, we show how the phenomenon of cognitive automation can be instantiated by Machine Learning-facilitated BPA systems that operate along the spectrum of lightweight and heavyweight IT implementations in larger IS ecosystems. Based on this, we describe the relevance and opportunities of cognitive automation in Information Systems research.

Crowdfunding is now established as a valid alternative to conventional methods of financing for startups. Unfortunately, to date, research has not investigated how backers can be encouraged to support entrepreneurs beyond funding. The aim of this study is to design and evaluate certain design elements for reward-based crowdfunding platforms that can engage backers in co-creational activities for product development. The study uses a design science research (DSR) approach and the theoretical concept of psychological ownership to inform a new design and then experimentally test that design. The results suggest that the derived artifacts positively influence co-creational activities in crowdfunding and that feelings of psychological ownership play an important mediating role. The contribution of this research is threefold. First, this paper extends crowdfunding’s application potential from merely a method of financing to a method of value creation with customers for product development. Second, the study advances DSR by applying a new DSR approach that shows whether a design performs as hypothesized by theory. Third, this research allows the exploration of backers’ individual behavior as opposed to their collective behavior.

Research has a long history of discussing what is superior in predicting certain outcomes: statistical methods or the human brain. This debate has repeatedly been sparked off by the remarkable technological advances in the field of artificial intelligence (AI), such as solving tasks like object and speech recognition, achieving significant improvements in accuracy through deep-learning algorithms (Goodfellow et al. 2016), or combining various methods of computational intelligence, such as fuzzy logic, genetic algorithms, and case-based reasoning (Medsker 2012). One of the implicit promises that underlie these advancements is that machines will 1 day be capable of performing complex tasks or may even supersede humans in performing these tasks. This triggers new heated debates of when machines will ultimately replace humans (McAfee and Brynjolfsson 2017). While previous research has proved that AI performs well in some clearly defined tasks such as playing chess, playing Go...

In this research, we explore the unique case of JumpStartFund, a new crowdfunding platform that is used to develop the Hyperloop project. To this end, we employ an in-depth single case study to examine the participation architecture of the platform as well as the Hyperloop campaign content, based on which we derive a new crowdfunding model. The derived crowdfunding model differs from existing crowdfunding models in that it allows entrepreneurs to develop their business with the crowdmore actively. Our research has important implications for research and practice. First, we introduce a new crowdfunding model that expands the boundaries of existent models. Second, we explain how our model helps to more efficiently leverage the potential inherent in the crowd thereby redefining entrepreneurial success within crowdfunding. Third, we discuss how our findings contribute to existent research within the context of crowdsourcing.

In this research, we explore the unique case of JumpStartFund, a new crowdfunding platform that is used to develop the Hyperloop project. To this end, we employ an in-depth single case study to examine the participation architecture of the platform as well as the Hyperloop campaign content, based on which we derive a new crowdfunding model. The derived crowdfunding model differs from existing crowdfunding models in that it allows entrepreneurs to develop their business with the crowdmore actively. Our research has important implications for research and practice. First, we introduce a new crowdfunding model that expands the boundaries of existent models. Second, we explain how our model helps to more efficiently leverage the potential inherent in the crowd thereby redefining entrepreneurial success within crowdfunding. Third, we discuss how our findings contribute to existent research within the context of crowdsourcing.

One of the most critical tasks for startups is to validate their business model. Therefore, entrepreneurs try to collect information such as feedback from other actors to assess the validity of their assumptions and make decisions. However, previous work on decisional guidance for business model validation provides no solution for the highly uncertain and complex context of early-stage startups. The purpose of this paper is, thus, to develop design principles for a Hybrid Intelligence decision support system (HI-DSS) that combines the complementary capabilities of human and machine intelligence. We follow a design science research approach to design a prototype artifact and a set of design principles. Our study provides prescriptive knowledge for HI-DSS and contributes to previous work on decision support for business models, the applications of complementary strengths of humans and machines for making decisions, and support systems for extremely uncertain decision-making problems.

In an atmosphere of rapidly changing business environments and intense competition, adequate and timely business models are crucial for companies. Current research mainly focuses on business model development that often neglects the legacy of established companies. The paper at hand addresses this research gap by a process design which allows established companies to rethink, improve, and continually innovate their business models. Following a design science research approach, requirements for improving business models are identified by the analysis of existing literature and by expert interviews. Collaboration Engineering and a multilevel evaluation are applied to create a continuous and implementable process design for business model improvement – including specific activities, instructions, and tools. The process design represents a nascent design theory in form of an “invention” type of knowledge contribution. Moreover, going beyond existing literature, the importance of collaboration between participants in a business model improvement project is highlighted. From a practical perspective, the developed process design enables companies for continuous and recurring business model improvement without the ongoing support of professional moderators or consultants.

While collaborative business modeling (CBM) constitutes a promising new approach for opening up a company’s innovation process, existing literature lacks empirical evidence of the effects related to this approach. Drawing on related literature on the quality of creative output, this paper proposes that in the context of a CBM initiative, the integration of customers will improve the quality of the generated output. As indicated by the results of our empirical evaluation, customers are indeed capable of developing high quality business models and are able to outperform company experts when it comes to the task of developing new business models.