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Artificial Intelligence enables innovative applications, and applications based on Artificial Intelligence are increasingly important for all aspects of the Digital Economy. However, the question of how AI resources such as tools and data can be linked to provide an AI-capability and create business value is still open. Therefore, this paper identifies the value-creating mechanisms of connectionist artificial intelligence using a capability-oriented view and points out the connections to different kinds of business value. The analysis supports an agenda that identifies areas that need further research to understand the mechanism of value creation in connectionist artificial intelligence.
This paper examines the efficacy of social media systems in customer complaint handling. The emergence of social media, as a useful complement and (possibly) a viable alternative to the traditional channels of service delivery, motivates this research. The theoretical framework, developed from literature on social media and complaint handling, is tested against data collected from two different channels (hotline and social media) of a German telecommunication services provider, in order to gain insights into channel efficacy in complaint handling. We contribute to the understanding of firm’s technology usage for complaint handling in two ways:
(a) by conceptualizing and evaluating complaint handling quality across traditional and social media channels and (b) by comparing the impact of complaint handling quality on key performance outcomes such as customer loyalty, positive word-of-mouth, and crosspurchase intentions across traditional and social media channels.
While there has been increased digitization of private homes, only little has been done to understand these specific home technologies, how they serve consumers, among other issues. “Smart home technology” (SHT) refer to a wide range of artifacts from cleaning aids to energy advisors. Given this breadth, clarity surrounding the key characteristics and the multi-faceted impact of SHT is needed to conduct more directed research on SHT. We propose a taxonomy to help outline the salient intended outcomes of SHT. Through a process involving five iterations, we analyzed and classified 79 technologies (gathered from literature and industry reports). This uncovered seven dimensions encompassing 20 salient characteristics. We believe these dimensions/characteristics will help researchers and organizations better design and study the impacts of these technologies. Our long-term agenda is to use the proposed taxonomy for an exploratory inquiry to understand tensions occurring when personal and sustainability-related outcomes compete.
Theoretical foundation, effectiveness, and design artefact for machine learning service repositories
(2022)
Machine learning (ML) has played an important role in research in recent years. For companies that want to use ML, finding the algorithms and models that fit for their business is tedious. A review of the available literature on this problem indicates only a few research papers. Given this gap, the aim of this paper is to design an effective and easy-to-use ML service repository. The corresponding research is based on a multi-vocal literature analysis combined with design science research, addressing three research questions: (1) How is current white and gray literature on ML services structured with respect to repositories? (2) Which features are relevant for an effective ML service repository? (3) How is a prototype for an effective ML service repository conceptualized? Findings are relevant for the explanation of user acceptance of ML repositories. This is essential for corporate practice in order to create and use ML repositories effectively.
The time has come : application of artificial intelligence in small- and medium-sized enterprises
(2022)
Artificial intelligence (AI) is not yet widely used in small- and medium-sized industrial enterprises (SME). The reasons for this are manifold and range from not understanding use cases, not enough trained employees, to too little data. This article presents a successful design-oriented case study at a medium-sized company, where the described reasons are present. In this study, future demand forecasts are generated based on historical demand data for products at a material number level using a gradient boosting machine (GBM). An improvement of 15% on the status quo (i.e. based on the root mean squared error) could be achieved with rather simple techniques. Hence, the motivation, the method, and the first results are presented. Concluding challenges, from which practical users should derive learning experiences and impulses for their own projects, are addressed.
IT Governance (ITG) is crucial due to its significant impact on enabling innovation and enhancing firm performance. Hence, in the last decade ITG has become important in both academic and in practical research. Although several studies have investigated individual aspects of ITG success and its impact on single determinants, the causal relationship of how ITG promotes firm performance remains unclear. Thus, a more comprehensive understanding about the link between ITG and firm performance is needed. To address this gap, this research aims at understanding how ITG and firm performance are related. Therefore, we conducted a systematic literature review (1) to create an overview on how current research structures the link between ITG mechanisms and firm performance, (2) to uncover key constructs as potential mediators or moderators on the general link between ITG and performance, and (3) to set the basis for future studies on the ITG-firm performance relationship.
Study programs in higher education have to reflect important societal and industrial challenges to prepare the next generations of professionals for future tasks. The focus of this paper is the challenge of digitalization and digital transformation. The paper proposes the IS education profile of a Digital Business Architect (DBA). The study program emphasizes design thinking, model centricity, and capability thinking as a response to domain requirements from digital transformation and educational system and structure requirements. Experiences in implementing the DBA include the need for integrating deductive and inductive teaching, a strong basis in real-world cases, and collaborative learning approaches to develop adequate competences in business model management, enterprise modeling, enterprise architecture management, and capability management.
With significant advancements in digital technologies, firms find themselves competing in an increasingly dynamic business environment. Therefore, the logic of business decisions is based on the agility to respond to emerging trends in a proactive way. By contrast, traditional IT governance (ITG) frameworks rely on hierarchy and standardized mechanisms to ensure better business/IT alignment. This conflict leads to a call for an ambidextrous governance, in which firms alternate between stability and agility in their ITG mechanisms. Accordingly, this research aims to explore how agility might be integrated in ITG. A quantitative research strategy is implemented to explore the impact of agility on the causal relationship among ITG, business/IT alignment, and firm performance. The results show that the integration of agile ITG mechanisms contributes significantly to the explanation of business/IT alignment. As such, firms need to develop a dual governance model powered by traditional and agile ITG mechanisms.
Facing ever-looming climate change, studying the drivers for individuals' Information Systems (IS) Use to reduce environmental harm gains momentum. While extant research on the antecedents of sustainable IS Use has focused on specific theories, interventions, contexts, and technologies, a holistic understanding has become increasingly elusive, with a synthesis remaining absent. We employ a systematic literature review methodology to shed light on the driving antecedents for sustainable IS Use among individual consumers. Our results build on findings of 29 empirical studies drawn from 598 articles retrieved from our premier outlets and a forward/backward search. The analysis reveals six salient complementary antecedents: Relief, Empowerment, Default, User-centricity, Salience, and Encouragement. We recommend considering these concepts when developing, deploying, promoting, or regulating digital technologies to mitigate individual consumers' emissions. Along with memorable and implementable concepts, our theoretical framework offers a novel conceptualization and four promising avenues for researchers on sustainable IS Use.