Towards a Governance of Low-Code Development Platforms Using the Example of Microsoft PowerPlatform in a Multinational Company

The advantages of low-code platforms include the ability to better manage corporate processes. These processes can quickly become customized and business critical. Consequently, governance of low-code development platforms gains increasing importance in the IT sector. This paper contributes to the design of a governance for low-code platforms using the example of Microsoft PowerPlatform through the action-design- research-paradigm within a consumer goods corporation. The paper shows both the relationship between IT governance and low-code platforms and what challenges this poses, as well as the importance of governance of low-code platforms in relation to the field of end-user computing. This work aims at developing governance for low-code platforms, and evaluates it using several methods. Based on the results of the naturalistic evaluation, design principles for the development of a governance for low-code platforms are derived. The principles summarize suggestions for designing such governance, providing evidence-based design knowledge for developing governance of low-code platforms

Design Knowledge for the Lifecycle Management of Conversational Agents

Organizations spend extensive resources on artificial intelligence (AI) solutions in customer service in order to remain customer-focused and competitive. A rising language-based application of AI emerges in the context of conversational agents (CAs), such as chatbots, which represent increasingly intelligent, autonomous, scalable, and cost-effective service platforms. However, AI-based CAs bring new organizational challenges. They are underrepresented in current research, leading to many unanswered questions and research potential regarding the management of their introduction, operation, and improvement. To address this issue, we provide design knowledge that considers the organizational perspective of CAs. Therefore, we conducted a systematic literature review (SLR) and qualitative interview study to reveal and analyze individual issues and challenges, develop meta-requirements, and finally, use them to create design principles. We contribute to the emerging field of CAs that has previously focused mainly on the individual, behavioral, interactional, or technical design

Leveraging the Potential of Conversational Agents: Quality Criteria for the Continuous Evaluation and Improvement

Contemporary organizations are increasingly adopting conversational agents (CAs) as intelligent and natural language-based solutions for providing services and information. CAs promote new forms of personalization, speed, cost-effectiveness, and automation. However, despite their hype in research and practice, organizations fail to sustain CAs in operations. They struggle to leverage CAs’ potential because they lack knowledge on how to evaluate and improve the quality of CAs throughout their lifecycle. We build on this research gap by conducting a design science research (DSR) project, aggregating insights from the literature and practice to derive a validated set of quality criteria for CAs. Our study contributes to CA research and guides practitioners by providing a blueprint to structure the evaluation of CAs to discover areas for systematic improvement