Now showing 1 - 5 of 5
  • Publication
    Stairway to Heaven or Highway to Hell: A Model for Assessing Cognitive Automation Use Cases
    Cognitive automation (CA) moves beyond rule-based business process automation to target cognitive knowledge and service work. This allows the automation of tasks and processes, for which automation seemed unimaginable a decade ago. To organizations, these CA use cases offer vast opportunities to gain a significant competitive advantage. However, CA imposes novel challenges on organizations’ decisions regarding the automation potential of use cases, resulting in low adoption and high project failure rates. To counteract this, we draw on an action research study with a leading European manufacturing company to develop and test a model for assessing use cases’ amenability to CA. The proposed model comprises four dimensions: cognition, data, relationship, and transparency requirements. The model proposes that a use case is less (more) amenable to CA if these requirements are high (low). To account for the model’s industry-agnostic generalizability, we draw on an internal evaluation within the action research company and three additional external evaluations undertaken by independent project teams in three distinct industries. From a practice perspective, the model will help organizations make more informed decisions in selecting use cases for CA and planning their respective initiatives. From a research perspective, the identified determinants affecting use cases’ amenability to CA will enhance our understanding of CA in particular and artificial intelligence as the driving force behind CA in general.
  • Publication
    Leveraging Low Code Development of Smart Personal Assistants: An Integrated Design Approach with the SPADE Method
    Smart personal assistants (SPAs) promise individualized user interactions owing to their varying interaction possibilities, knowledgeability, and human-like behaviors. To support the widespread adoption and use of SPAs, organizations such as Google or Amazon provide low code environments that support the development of SPAs (e.g., for Google Home or Amazon’s Alexa). These so-called low code platforms enable domain experts (e.g., business users without programming skills or experience) to develop SPAs for their purposes. However, using these platforms alone does not guarantee a useful and good conversation with novel SPAs due to non-intuitive design choices. Following a design science research approach, we propose the Smart Personal Assistant for Domain Experts (SPADE) method to address the missing link. This method supports domain experts in the development and contextualization of sophisticated SPAs for various application scenarios and focuses especially on conversational and anthropomorphic design steps. Our proof of concept and proof of value results show that SPADE is useful for supporting domain experts to create effective SPAs in different domains beyond private set-ups.
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    Scopus© Citations 6
  • Publication
    Understanding the Design Elements Affecting User Acceptance of Intelligent Agents: Past, Present and Future
    Intelligent agents (IAs) are permeating both business and society. However, interacting with IAs poses challenges moving beyond technological limitations towards the human-computer interface. Thus, the knowledgebase related to interaction with IAs has grown exponentially but remains segregated and impedes the advancement of the field. Therefore, we conduct a systematic literature review to integrate empirical knowledge on user interaction with IAs. This is the first paper to examine 107 Information Systems and Human-Computer Interaction papers and identified 389 relationships between design elements and user acceptance of IAs. Along the independent and dependent variables of these relationships, we span a research space model encompassing empirical research on designing for IA user acceptance. Further we contribute to theory, by presenting a research agenda along the dimensions of the research space, which shall be useful to both researchers and practitioners. This complements the past and present knowledge on designing for IA user acceptance with potential pathways into the future of IAs.
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    Scopus© Citations 27
  • Publication
    How Conversational Agents Relieve Teams from Innovation Blockages
    Innovation is one of the most important antecedents of a company's competitive advantage and long-term survival. Prior research has alluded to teamwork being a primary driver of a firm's innovation capacity. Still, many firms struggle with providing an environment that supports innovation teams in working efficiently together. Thereby, a team's failure can be attributed to several factors, such as inefficient working methods or a lack of internal communication that leads to so-called innovation blockages. There are a number of approaches that are targeted at supporting teams to overcome innovation blockages, but they mainly focus on the collaboration process and rarely consider the needs and potentials of individual team members. In this paper, we argue that Conversational Agents (CAs) can efficiently support teams in overcoming innovation blockages by enhancing collaborative work practices and, specifically, by facilitating the contribution of each individual team member. To that end, we design a CA as a team facilitator that provides nudges to reduce innovation blocking actions according to requirements we systematically derived from scientific literature and practice. Based on a rigorous evaluation, we demonstrate the potential of CAs to reduce the frequency of innovation blockages. The research implications for the development and deployment of CAs as team facilitators are explored.
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