Deploying a Model for Assessing Cognitive Automation Use Cases: Insights from Action Research with a Leading European Manufacturing Company

Cognitive automation moves beyond rule-based automation and thus imposes novel challenges on organizations when assessing the automation potential of use cases. Thus, we present an empirically grounded and conceptually operationalized model for assessing cognitive automation use cases, which consists of four assessment dimensions: data, cognition, relationship, and transparency requirements. We apply the model in a real-world organizational context in the course of an action research project at the customer service department of ManuFact AG, and present unique empirical insights as well as the impact the application of the model had on the organization. The model shall help practitioners to make more informed decisions on selecting use cases for cognitive automation and to plan respective endeavors. For research, the identified factors affecting the suitability of a use case for cognitive automation shall deepen our understanding of cognitive automation in particular, and AI as the driving force behind cognitive automation in general

Opening the Black Box of Music Royalties with the Help of Hybrid Intelligence

The ever-increasing complexity of the music industry and the intensified resentment of artists towards collecting societies call for a transformation and a change of behavior within the music ecosystem. This article introduces a hybrid intelligence system, that ameliorates the current situation by combining the intelligence of humans and machines. This study proposes design requirements for hybrid intelligence systems in the music industry. Using a design science research approach, we identify design requirements both inductively from expert interviews and deductively from theory and present a first prototypical instantiation of a respective hybrid intelligence system. Overall, this shall enrich the body of knowledge of hybrid intelligence research by transferring its concepts into a new context. Furthermore, the identified design requirements shall serve as a foundation for researchers and practitioners to further explore and design hybrid intelligence in the music industry, and beyond

An Investigation of Why Low Code Platforms Provide Answers and New Challenges

Although the idea of low code development is not new, the market for these oftentimes platform-based development approaches is exponentially growing. Especially factors such as increasing affinity for technology development across all user groups, consumerization of development, and advancing digitalization are opening a new target group for the low code movement. The broad application possibilities of low code, as well as the benefits, are therefore getting more important for businesses. Especially for small and medium-sized enterprises (SMEs), low code constitutes a promising avenue to survive and succeed in the rapidly changing world. However, a clear understanding regarding the application of this paradigm of software development in SMEs is still missing. To provide a coherent understanding of the phenomenon low code in SMEs, we review extant literature and conduct interviews, identifying potential application domains and conceptualizing the benefits and challenges of low code from a holistic perspective

FASTER, CHEAPER, BETTER? ANALYZING HOW LOW CODE DEVELOPMENT PLATFORMS DRIVE BOTTOM-UP INNOVATION

Recent years have seen a growing adoption of Low Code Development Platforms (LCDPs) in organizations. The increasing affinity for technology development across all user groups, consumerization of development, and advancing digitalization are opening up a new target group for the low code movement. This change in software development allows bottom-up user innovators within a company to leverage their domain knowledge and quickly deploy much-needed digital services. However, a clear understanding of this paradigm of software development in organizations and the influence on end-user acceptance is still missing. In this paper, we present the results of an interview study conducted with 18 LCDP experts and discuss the implications of our findings, highlighting the role of LCDPs and context in bottom-up innovation as well as user-centricity. Our research contributes to the literature on LCDPs and offers valuable insights for organizations looking to leverage their workforce\u27s innovative potential

Artificial Socialization? How Artificial Intelligence Applications Can Shape A New Era of Employee Onboarding Practices

Onboarding has always emphasized personal contact with new employees. Excellent onboarding can, for instance, extend an employee's stay, and improve loyalty. Even in a physical setting, the onboarding process is demanding for the newcomer and the onboarding organization. However, COVID-19 has made this process even more challenging by forcing a rapid shift from offline to online organizational onboarding practices. Organizations are adopting new technologies, such as artificial intelligence (AI), to support work processes during the pandemic, which could shape a new era of work practices. However, it has not been studied how AI applications can or should support onboarding. Therefore, our research conducts a literature review on current onboarding practices and uses expert interviews to evaluate AI's potential and pitfalls for each action. We contribute to the literature by presenting a holistic state-of-the-art picture of onboarding practices and evaluating potential application areas of AI in the onboarding process

SPAM – A Process Model for Developing Smart Personal Assistants

Information technology capabilities are growing at an impressive pace and increasingly overstrain the cognitive abilities of users. User assistance systems such as online manuals try to help the user in handling these systems. However, there is strong evidence that traditional user assistance systems are not as effective as intended. With the rise of smart personal assistants, such as Amazon’s Alexa, user assistance systems are becoming more sophisticated by offering a higher degree of interaction and intelligence. This study proposes a process model to develop Smart Personal Assistants. Using a design science research approach, we first gather requirements from Smart Personal Assistant designers and theory, and later evaluate the process model with developing an Amazon Alexa Skill for a Smart Home system. This paper contributes to the existing user assistance literature by offering a new process model on how to design Smart Personal Assistants for intelligent systems

ICT-enabled job crafting: How Business Unit Developers use Low-code Development Platforms to craft jobs

Recently, businesses are introducing low-code development platforms (LCDP) that enable employees with little to no development expertise to develop their own systems to improve their work. These so-called business unit developers (BUDs) possess necessary domain knowledge to understand how to use LCDPs to create useful (self-) services. Using job resource demand theory and the job crafting model, we conceptualize that BUDs use of LCDPs can be framed using the theoretical lens of job crafting. Job crafting stems from vocational psychology and provides well-researched positive consequences, such as wellbeing and meaningfulness. Thus, our research objective is to understand how BUDs can use LCDPs to job craft to gain access to positive job crafting consequences. We interviewed 17 experts across three organizations that employ an LDCP for chatbots. Our results suggest that job crafting is a suitable framework for understanding the effects of LCDP use