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Artificial Intelligence (AI) shows great potential to tackle environmental sustainability issues that are critical to the survival of Humanity and Planet Earth. However, the development and use of AI causes indirect emissions leading to detrimental effects on the environment. Therefore, it is important for organizations, researchers, and practitioners in the Information Systems (IS) domain to understand both the positive and negative effects of AI on the environment. This article contributes to this topic by performing a theoretical review of the literature at the intersection of AI and Sustainability to determine the current research streams. Further, this article adopts the affordance theory as a theoretical lens with the goal to identify the affordances of Sustainable AI – a field that encompasses the research areas ‘AI for Sustainability as well as ‘Sustainability of AI’ – in the Green IS community. The identified affordances would enable researchers and practitioners to design and use Sustainable AI systems.

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Conference or Workshop Item
Advances in Natural Language Processing offer techniques to de- tect the empathy level in texts. To test if individual feedback on certain students’ empathy level in their peer review writing pro- cess will help them to write more empathic reviews, we developed ELEA, an adaptive writing support system that provides students with feedback on the cognitive and emotional empathy structures. We compared ELEA to a proven empathy support tool in a peer review setting with 119 students. We found students using ELEA wrote more empathic peer reviews with a higher level of emotional empathy compared to the control group. The high perceived skill learning, the technology acceptance, and the level of enjoyment provide promising results to use such an approach as a feedback application in traditional learning settings. Our results indicate that learning applications based on NLP are able to foster empathic writing skills of students in peer review scenarios.

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Many industries are affected by the shift to platform business models and leveraging network effects is vital for every single company. At the same time, latest research shows that many companies, in particular established pipeline businesses, struggle with this new notion of doing business. Building upon the success of the Business Model Navigator, we have developed the Platform Navigator – a toolbox to help you design and implement platform business models in your company. By reviewing the most important literature and studying more than 150 cases, we have identified 88 pattern cards across five phases. Not all patterns will be helpful for your business and the patterns are certainly not exhaustive. But we believe that every manager should be aware of them to sustain competitive advantage. Thus, the pattern cards and canvas will help you navigate through the Platform Economy.

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Viele CIOs (Chief Information Officer) in Unternehmen haben in der Pandemie einen hervorragenden Job gemacht. In der Zeit nach der Pandemie gilt es, diesen „Rückenwind“ und die Position des CIO neu zu definieren. Vor diesem Hintergrund wurden fünf CIOs, Hanna Hennig von der Siemens AG, Andreas Maier von der AXA Schweiz, Michael Müller-Wünsch von OTTO, Rolf Olmesdahl, ehemals Raiffeisen Schweiz, Ursula Soritsch-Renier von Saint-Gobain Paris, und ein Executive-Search-Spezialist, Patrick Naef, Boyden AG, gefragt wie sie die Zukunft des CIO sehen. Alle sechs Persönlichkeiten, die an dem Dialog teilnahmen, sind übereinstimmend der Meinung, dass es auch noch 2030 CIOs geben wird und sie auf der einen Seite verstärkt Treiber der digitalen Transformation in ihrem Unternehmen sein sollten und sie auf der anderen Seite nach wie vor Verantwortung für das Funktionieren der digitalen Infrastruktur tragen.

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Volatility, uncertainty, complexity, and ambiguity (VUCA) are drivers in today's business world. To perform amid this accelerated change and the digitalization progress, organizations are implementing agility. However, such an implementation does not happen without stumbling blocks and some fail. One reason for this is actors’ agile mindset (AM), which is necessary to deal succefully within a VUCA environment. Knowledge of the AM is in its infancy and conceptualization and measuring tools for it are lacking. Furthermore, the relation of the AM in terms of strategic agility and performance is still unclear. Our study aims to close these gaps. We examine AM through 15 interviews and a survey (N = 449) to predict strategic agility and performance. As a result, we conceptualize AM as an attitude that comprises four dimensions: attitude towards 1) learning spirit, 2) collaborative exchange, 3) empowered self-guidance, and 4) customer co-creation. Furthermore, we describe how actors with an AM deal with new technologies. We found that AM affects organizational performance mediated by strategic agility. These findings contribute to the agility and management research by providing a conceptualization and measuring instrument for AM. Furthermore, its relevance for strategic agility is explained and its relationship with organizational performance outlined

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Obwohl sich die Rolle und Bedeutung der IT in den meisten Unternehmen stark verändert hat, folgt die Strukturierung von CIO-Bereichen (und ihrer Wertbeiträge) meist noch einem funktionalen Paradigma – unter Bezugnahme auf „was wird gemacht“ oder „wie wird es gemacht“, manchmal auch „für wen wird es gemacht“. Eine funktionale bzw. ergebnisorientierte Strukturierung findet sich mittelbar auch in Ansätzen, welche die Wertschöpfungskette in den Mittelpunkt stellen oder agile Gestaltungsprinzipien berücksichtigen.Wir diskutieren bestehende Ansätze und schlagen ein neues Strukturierungsmodell vor, das die Aktivitäten des CIO-Bereichs aus der Perspektive „welcher Wertbeitrag wird erreicht“ (bzw. welche strategische Wirkung wird angestrebt) unterscheidet. Das sich ergebende Wirkungsorientierte Portfolio wird dabei in den Dimensionen Wirkungsbreite, Wirkungszeitraum und Wirkungstiefe abgebildet. Ausgehend von der Demonstration bestimmter Aspekte dieses Perspektivenwechsels in Form von zwei Anwendungsfällen werden die Potenziale und Konsequenzen einer wirkungsorientierten Strukturierung des CIO-Bereichs z. B. für die Kommunikation des CIO-Wertbeitrags, die Koordination mit anderen Führungsfunktionen und die Organisation von „Business Technology“ diskutiert.

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get_appJenny Zimmermann, Jonas Görgen, Emanuel de Bellis, Reto Hofstetter
Monograph
The Smart Products Report 2022, now in its second edition, is based on a representative study on the use and perception of smart products in Switzerland. It is published by the Institute of Behavioral Science and Technology at the University of St.Gallen as well as the Institute of Marketing and Analytics at the University of Lucerne in collaboration with Vorwerk AG. The Smart Products Report 2022 shows that smart products are widely used in Switzerland and are increasingly integrated into our everyday lives. Among the most frequently used smart products are smartwatches, robotic vacuum cleaners, and smart speakers. The findings also suggest that the perception of and relationship with these technologies is changing. For example, consumers perceive these technologies to increasingly take over the lead while consumers humanize their smart helpers by giving them nicknames. The widespread use and positive attitude toward smart products contrast personal and societal concerns. Therefore, smart products’ future success depends on every stakeholder recognizing and addressing both, the benefits perceived by consumers and their distinct concerns about smart products.

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The ability of students to self-monitor their learning paths is in demand as never before due to the recent rise of online education formats, which entails less interaction with lecturers. Recent advantages in educational process mining (EPM) offer new opportunities to monitor students’ learning paths by processing log data captured by technology-mediated learning environments. However, current literature falls short on providing user-centered design principles for IT-tools which can monitor learning paths using EPM. Hence, in this paper, we examine how to design a self-monitoring tool that supports students to evaluate their learning paths. Based on theoretical insights of 66 papers and nine user interviews, we propose seven design principles for an IT-tool which facilitates self-monitoring for students based on EPM. Further, we evaluate the design principles with seven potential users. Our results demonstrate a promising approach to help students improve their self-efficacy in their individual learning process using EPM.

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Driven by circumstances like the global pandemic many learners and educators realize the importance and value of self-regulated digital learning. To better support self-regulated learning, conversational agents have become more relevant. Conversational agents can act as tutor or as learning mate for learners. Although conversational agents have potential to better support self-regulated learning processes, challenges exist requiring implications about how to make these interactions more engaging and supportive. This study discusses the value of gamified conversational learning chatbots that use game elements to engage learners to guide researchers and practitioners to design conversational agents that effectively motivate learners and provide self-regulated learning at the same time. Therefore, we propose a systematically developed framework for gamifying educational conversational agents and contribute to theory by consolidating several theories about games, digital learning, and conversational agents and support practitioners by providing implications about what to care about when gamifying conversational agents

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Today’s servitized and digitalized society has significant implications for the economic system as value creation increasingly shifts towards digital services. Organizations are increasingly relying of artificial intelligence, which enables them to operate with novel technological artifacts like conversational agents (CA). These human-like AI-driven artifacts open new possibilities and channels for service providers to scale up their business even further and to create a business value or even to make processes more efficient. While we witness the results of that each day, we do not fully understand how such CAs can contribute to scaling up a business. Therefore, we conduct an analysis of service research and popular CAs to determine the status quo and highlight opportunities for scaling services with CAs. We contribute to theory by clarifying the meaning of scalability in combination with CAs and support practitioners by providing an overview about how organizations successfully scale their CAs.

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As organizations are challenged with volatility, uncertainty, complexity and ambiguity (VUCA), developing agile capabilities becomes the first priority for most organizations to innovate and respond rapidly to external changes (Klimenko, Winter, & Rohner, 2019). However, a shift in management toward greater agility at the enterprise level poses major challenges for organizations trying to transform their slow-moving, top-down bureaucratic practices (Leybourn, 2019). In this dissertation project the author designed a Corporate Agility Maturity Model to support organizations in their transformational programs by providing guidance on systematically developing Corporate Agility capabilities in a certain sequence that follows the organizational learning journey. The author captured the Corporate Agility as an organizational phenomenon and, therefore, focused on Agility not on the team level or individual level, but at the highest organizational level, where enterprise-wide decisions are made for the entirety of the organization. Although maturity models are an established instrument to devise development paths, currently available maturity models often focus on the control of certain capabilities (doing things right) (Winter & Aier, 2020). The proposed Corporate Agility Maturity Model identifies the organizational Corporate Agility maturity level and derives a roadmap for developing the Corporate Agility capabilities in a sequence appropriate for a given type of organization (doing the right things).

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The uprise of the internet of things (IoT) has stimulated both digital platform natives and industry incumbents to compete for IoT platform leadership. While digital natives, such as Microsoft, Google, or Amazon denote experienced and well-studied platform owners, industry incumbents, such as IBM, General Electric, and AT&T have to learn how to extend their established pipeline businesses with IoT platforms. As socio-technical systems, IoT platforms offer industry incumbents the unique opportunity to profit from value cocreation, i.e., the joint development of products and services with third parties. While scholars have studied multiple mature digital platforms, research on platform establishment and industry incumbents capabilities to foster value cocreation is scarce. Thus, this thesis asks: How can industry incumbents successfully establish IoT platforms for value cocreation? Drawing on case study research, three pillars answer this overarching research question. Pillar one examines platform governance to understand what strategies support the value cocreation process and how they address specific challenges in enterprise IoT. Pillar two deals with the challenge of platform growth in the establishment phase. On the one hand, third parties decisions to join IoT platforms are studied. On the other hand, two modes that foster early platform growth are proposed. Pillar three explores how industry incumbents develop platform capabilities in form of organizational routines and how they aid their business transformations to run both pipelines and platforms. Overall, the results of this dissertation contribute to platform research and its successful establishment from a value cocreation perspective. In that, they extend prior findings on platform governance, growth, and capabilities. While the results are insightful for all stakeholders of complex platforms, such as IoT platforms, they particularly address industry incumbents and the shift in their role, and the capabilities needed to actively foster value cocreation. Thus, managers can act upon the recommendations presented in this thesis when establishing their IoT platforms. However, future research is needed to find additional success factors to thrive for IoT platform leadership.

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The Internet of Things (IoT) offers product companies the opportunity to develop an IoT business. Existing performance measurement systems (PMS) are unsuitable for measuring and managing the business logic of IoT business. Based on research conducted with 31 product companies, we present three measurement traps, a key performance indicators (KPI) set suited for steering IoT business in product companies, and three recommendations for implementing the KPI set. Companies can use the KPI set to manage their IoT businesses more effectively and avoid the measurement traps.

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get_appKarolina Marie Luise Schabert, Laura Raschle, Anna Fredholm, Lorenzo Pedrazzoli, Georgine Settelen, Annamina Rieder, Reinhard Jung
Conference or Workshop Item
Nudging und die Frage nach seiner Wirksamkeit wird im digitalen Zeitalter immer wichtiger, da Entscheidungen immer häufiger in digitalen Umgebungen getroffen werden. Gleichzeitig gibt es kaum Forschung zu den unbeabsichtigten und schädlichen Folgen von Nudging, auch als Backfiring bezeichnet. Das Paper beschäftigt sich deshalb mit der Rolle von Reaktanz im Zusammenhang mit Scarcity-Nudges. Es wurde ein Online-Experiment (n=180) auf einer fiktiven Hotelbuchungswebsite durchgeführt und der Einfluss zweier Varianten eines Scarcity-Nudges (Demand-Side vs. Supply-Side) auf die Reaktanz und die Kaufabsicht untersucht. Aufgezeigt werden konnte, dass die Reaktanz die Kaufabsicht, ausgelöst durch den Scarcity-Nudge auf der Supply-Side, reduziert. Auf der Demand-Side konnte kein Einfluss der Reaktanz auf die Kaufabsicht durch Scarcity-Nudges festgestellt werden.

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Wie sehen gelungene Studienprogramm-Reformen an einer spezifischen Hochschule aus? Welche Faktoren sind dabei wichtig und wie kann üblichen Herausforderungen erfolgreich begegnet werden? In diesem Beitrag stellen wir die Ergebnisse der Evaluation einer Studienprogramm-Reform an der Universität St. Gallen (HSG) dar. Ausgehend vom aktuellen Stand der wissenschaftlichen Diskussion um Studienprogramm-Reformen, werden Faktoren einer gelungenen Reform aus zwei Befragungen abgeleitet, die diese Reform begleiteten.

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get_appChristian Engel, Philipp Ebel, Jan Marco Leimeister
Journal paper
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.

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The increasing digitalization and automatization in the manufacturing industry as well as the need to learn on the job has reinforced the need for much more granular learning, which has not yet impacted the design of learning materials. In this regard, granular learning concepts require situated learning materials to support self-directed learning in the workplace in a targeted manner. Co-creation approaches offer promising opportunities to support employees in the independent design of such situated learning materials. Using an action-design research (ADR) approach, we derived requirements from co-creation concepts and practice by conducting focus group workshops in manufacturing and vocational training schools to develop design principles for a co-creation system that supports employees through the creation process of work-process-related learning material. Consequently, we formulate four design principles for the design of a collaborative learning and qualification system for manufacturing. Using an innovative mixed methods approach, we validate these design principles and design features to demonstrate the success of the developed artifact. The results provide insights regarding the design of a co-creation system to support learners in the co-creation of learning material with the consideration of cognitive load (CL). Our study contributes to research and practice by proposing novel design principles for supporting employees in peer creation processes. Furthermore, our study reveals how co-creation systems can support the collaborative development of learning materials in the work process.

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Design science projects are of great interest in information systems (IS) research. Typically, design-oriented projects generate valuable design knowledge through the design and possible instantiation of artifacts. Although designing novel artifacts and accumulating design knowledge is common practice in IS, there is still limited shared knowledge about the distinctive characteristics of design knowledge to facilitate its accumulation. To address this issue, we develop a design knowledge taxonomy and contribute to a deeper understanding of design knowledge properties. The taxonomy is grounded on a systematic literature review, followed by a combination of empirical-to-conceptual and conceptual-to-empirical iterations. We evaluate the taxonomy by interviewing six domain experts and demonstrate its practical application and utility. Thus, the taxonomy consists of key dimensions and characteristics of design knowledge and contributes to a better scientific understanding of its characteristics. Practitioners can use the taxonomy as an instrument to further understand, design, and accumulate design knowledge.

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To ensure that an intended target group accepts and uses an information system (IS) is a major challenge for service systems engineering and a key interest in IS research. On the one hand, individuals’ cultural values affect their willingness to use an IS; on the other hand, information technology (IT) is neither value-neutral and, thus, also affects IT acceptance and usage. Therefore, the adaptation of IS should consider both sources of value. Thus, in this paper, we present the theory-driven design of a method for culture-sensitive IS adaptation that draws on IT-culture conflict theory. Our two-fold evaluation approach results show that the method enables to create feasible results for developing culture-sensitive design solutions for IS. As a theoretical contribution, we contribute to the exploration of culture in IS development; as a practical contribution, we provide guidance in how to adapt IS for specific target groups.

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As more and more organizations reach the limits of their internal capabilities to deal with the challenges induced by digital transformation, they are increasingly forced to seek external digitalization opportunities. In particular, small and medium enterprises are affected by this due to their limited human and financial resources. Currently, there is a lack of overview of options considering limited internal digital capabilities and resources. Thus, we choose an action design research approach to develop an external digitalization activity navigator. As a result, we derive five design principles for successful navigation and 30 activities, which are presented as design pattern cards. Our work can help practitioners and scholars alike to structure external digitalization activities. After discussing the insights, we outline directions for future research. We conclude by noting the managerial implications of our findings.

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Although the nexus of Design Thinking (DT) and corporate entrepreneurship is heralded to be promising, the concrete compositional architecture of how DT manifests in practice has received limited scholarly attention. Drawing on the argument that DT can facilitate intrapreneurial innovation as it enables effectual cognition, we developed a multidimensional assessment model that measures DT for intrapreneurial innovation in an organizational context and applied it via an online survey to 547 organizations of different sizes and industries. An analysis of the dimensional and sub-dimensional values obtained from the quantitative survey data in general, and with regard to industry and firm size types in detail, enriches our understanding of DT’s manifestation in practice. We provide practitioners a useful tool to assess, benchmark, plan, analyze, and communicate the use of DT for intrapreneurial innovation, and guide future DT and entrepreneurship researchers seeking practitioner-relevant insights with nine propositions derived from our observations.

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To equip students with practical capability to innovate, academic institutions are promoting industry collaboration projects where students use creative approaches, for example, design thinking, to solve complex business challenges. In creative work, the ability to reflect on the current team state and to continuously improve based on these insights is vital for effective teams. However, research on the role of digital technology to support collaborative reflection is still in its infancy. This study aims to present a digital solution that uses micro surveys and concepts of Educational Data Mining (EDM) to support collaborative reflection of students working in creativity-driven engineering projects. Using design science research, we identify design requirements of the InnoPulse tool, implement the corresponding design features and evaluate our digital solution in a real-world educational setting. Our findings pave the way for the potential of using EDM concepts to improve collaborative reflection of students using DT methods.

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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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Conference or Workshop Item
Innovation requires organizations to tap into the knowledge and creativity of teams. However, teams are confronted with massive amounts of data and information, necessitating a broad set of knowledge, methodologies, and approaches to solve problems and innovate. Consequently, team composition has become a critical challenge. Recent advances in artificial intelligence (AI) may assist in addressing this challenge. As AI is permeating both business and private sectors, organizational teams may be augmented with AI team members. However, given the nascent nature of this phenomenon, little is known about the specific roles and requirements for such AI teammates. Within an interview study we discover common challenges in teams and identify recurring capability gaps of participants and behaviors that negatively impact the team's collective performance. Based on our findings, we propose requirements for AI-based teammates to address these gaps and support beneficial collaboration between humans and AI in teams.

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get_appLino Markfort, Alexander Arzt, Philipp Kögler, Sven Jung, Heiko Gebauer, Sebastian Haugk, Christian Leyh, Felix Wortmann
Journal paper
Purpose – The emergence of Internet of Things (IoT) platforms in product companies opens up new data-driven business opportunities. This paper looks at the emergence of these IoT platforms from a business-model perspective. Design/methodology/approach – The study applies a mixed method with two research studies: Study I–a cluster analysis based on a quantitative survey, and Study II–case studies based on qualitative interviews. Findings – The findings reveal that there is no gradual shift in a company’s business model, but in fact three distinct and sequential patterns of business model innovations: (1) platform skimming, (2) platform revenue generation and (3) platform orchestration. Research limitations/implications – The results are subject to the typical limitations of both quantitative and qualitative studies. Practical implications – The results provide guidance to managers on how to modify the components of the business model (value proposition, value creation and/or delivery and profit equation) in order to enable platforms to advance. Social implications – As IoT platforms continue to advance, product companies achieve better performance in terms of productivity and profitability, and more easily secure competitive advantages and jobs. Originality/value – The paper makes three original contributions: (1) it is the first quantitative study on IoT platforms in product companies, (2) identifies three patterns of business model innovations and (3) offers a first process perspective for understanding the sequence of these patterns as IoT platforms advance.

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Design Thinking has become a well-established approach to solving wicked problems through creative and conceptual solutions. Thus, Design Thinking approaches usually end with finding novel solutions but do not offer support in the practical implementation of these solutions. To bridge the gap between finding creative solutions and implementing them into suitable end products, we see Design Patterns as a useful approach to combine the advantages of both sides—the human-centered Design Thinking approach and the practical implementation in system development. Design Patterns offer proven solutions to recurring problems and thus provide design knowledge to solve complex design problems. In this contribution, we demonstrate how Design Patterns act as a complement to Design Thinking by using the example of designing a lawful smart personal learning assistant. We use Design Thinking to extract the design solution of the lawful learning assistant and develop it with the help of Design Patterns. We demonstrate the use of Design Patterns by using the deletion routine Design Pattern as an example of how a Design Pattern can be used for lawful design in addition to their known fields of application in system development. The evaluation results show that the combination of Design Thinking and Design Patterns lead to an approach that not only identifies novel, complex solutions but also supports their practical implementation.

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The deployment of Artificial Intelligence (AI) in businesses is said to provide significant benefits to organizations. However, many businesses struggle to align single AI use cases with the overall strategic business value contribution. Thus, we investigate the strategic characteristics that determine the business value contribution of AI use cases at an organizational level. We draw on academic literature and 106 AI use cases to develop a conceptually sound and empirically grounded taxonomy of the organizational business value of AI use cases. With the developed taxonomy, decision-makers are presented with a tool to systematically align AI use cases with strategic objectives. Moreover, our findings reveal how an AI use case can generate different business value contributions in different contexts, which provides researchers with a conceptual frame for informing their empirical research endeavors at the organizational level.

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With looming uncertainties and disruptions in today’s global supply chains, such as lockdown measures to contain COVID-19, supply chain resilience has gained considerable attention recently. While decision-makers in procurement have emphasized the importance of traditional risk assessment, its shortcomings can be complemented by resilience. However, while most resilience studies are too qualitative in nature and abstract to inform supplier decisions, many quantitative resilience studies frequently rely on complex and impractical operations research models fed with simulated supplier data. Thus there is the need for an integrative, intermediate way for the practical and automated prediction of resilience with real-world data. We therefore propose a random forest-based supervised learning method to predict supplier resilience, outperforming the current human benchmark evaluation by 139 percent. The model is trained on both internal ERP data and publicly available secondary data to help assess suppliers in a pre-screening step, before deciding which supplier to select for a specific product. The results of this study are to be integrated into a software tool developed for measuring and tracking the total cost of supply chain resilience from the perspective of purchasing decisions.

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Although Enterprise Architecture Management (EAM) is a mature discipline and widely adopted in practice, surveys indicate effectivity barriers that, at least partially, appear to be a consequence of local decision makers’ non-compliance with enterprise-wide architectural guidelines. Several recent contributions aim at extending the portfolio of EAM interventions by applying informal control mechanisms. Although promising to extend EAM effectivity, informal interventions are apparently not much utilized in EAM practice. Based on the assumption that a comprehensive presentation of design knowledge for informal EAM interventions would support more widespread adoption, this paper integrates existing knowledge components to a coherent design approach. The proposal covers theoretical justification, conceptual foundations, a taxonomy of generic informal interventions, a catalogue of derived EAM intervention types, and a process to systematically instantiate and evaluate situation-specific informal interventions. Two Action Design Research projects in large companies are summarized as evaluative evidence for the potential that comprehensive in-formal intervention design has for improving EAM effectivity.

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Marketers are often older than the audiences they are trying to reach, making it a challenge to connect. A new study examines the marketing generation gap and suggests some ways to narrow it.

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In our digital world, all companies need IT support. The IT support staff is under high pressure solving user-based issues and facing an increase of heterogeneous systems. Hybrid intelligence could solve many issues due to the combination of machine power and the individual strengths of humans. As a part of a bigger design science research project, this paper derives requirements for an IT support system based on hybrid intelligence (ISSHI). 17 requirements from the literature and 21 requirements from 24 indepth interviews with IT support managers and support-agents from three different companies have been derived. These were evaluated and refined with a second interview series of five IT support stakeholders that led to a total of 24 consolidated requirements. Finally, these requirements were used to inform a system architecture for an ISSHI. This architecture shall serve as a foundation for future research directions regarding hybrid intelligence in IT support.

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Over the last decade, the importance of machine learning increased dramatically in business and marketing. However, when machine learning is used for decision-making, bias rooted in unrepresentative datasets, inadequate models, weak algorithm designs, or human stereotypes can lead to low performance and unfair decisions, resulting in financial, social, and reputational losses. This paper offers a systematic, interdisciplinary literature review of machine learning biases as well as methods to avoid and mitigate these biases. We identified eight distinct machine learning biases, summarized these biases in the cross-industry standard process for data mining to account for all phases of machine learning projects, and outline twenty-four mitigation methods. We further contextualize these biases in a real-world case study and illustrate adequate mitigation strategies. These insights synthesize the literature on machine learning biases in a concise manner and point to the importance of human judgment for machine learning algorithms.

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Residential heating, a major source of carbon emissions, is also a significant part of household costs, so reducing the consumption of energy for heating is of interest to both individuals and societies. Since the consequences of individual behavior related to heating are complex and not immediate, many people are unaware of them. In a longitudinal field experiment at a German real estate company, we evaluated two loss aversion nudges (one with a cost the other with a health-risk framing) toward sustainable heating behaviors. We find support for the cost framing nudge as the effectiveness of the nudge increased over the study period. Our findings have implications for research and for practitioners, particularly housing providers that seek ways to encourage pro-environmental behavior.

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Students that first learn about and wish to apply Design Science Research (DSR) perceive difficulties in communicating DSR research designs. This, however, is an important communication use case, since more senior design researchers need to gain a good understanding of the DSR research design propositions in order to provide adequate feedback and thus, support the new generation of design researchers. This study features an artefact that fills junior design researchers’ unsatisfied need for support in presenting DSR re-search designs. The artefact was built based on knowledge from the problem environment (i.e., a research methods course) and the emerging body of literature on DSR communication. It is evaluated in a natural field experiment, and the results indicate that the artefact is useful. A contribution of this article is the artefact itself, which is presented explicitly and can be re-used freely by DSR instructors.

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Gamification refers to the use of game-like elements in non-entertainment contexts to make activities more engaging and enjoyable to improve utilitarian outcomes. The gamification literature and the use of gamification in practice suggest that gamification can be a useful tool to support behavioral and psychological changes. Recent developments show that there is potential for new waves of gamification research. Therefore, we conducted a workshop at the International Conference on Wirtschaftsinformatik (WI) 2021 to discuss the future of gamification with interested scholars. The discussion with 25 gamification experts led to a research agenda that supports the need for adaptive and personalized gamification designs. Together with the experts, we identify three clusters for future research: 1) the personalization of gamification concepts, 2) theories and concepts for gamified human-computer interaction, and 3) the “dark side” of gamification (e.g., addiction). We also address what the gamification concept means. Aligned with the three clusters, we provide valuable starting points for future research inquiries to help researchers better understand the nature of gamification. We also discuss the capabilities and limits of gamification.

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get_appThiemo Wambsganss, Anuschka Schmitt, Thomas Mahning, Anja Ott, Sigita Soellner, Ngoc Anh Ngo, Jerome Geyer-Klingeberg, Janina Nakladal, Jan Marco Leimeister
Conference or Workshop Item
Educational process mining (EPM) offers new possibilities to discover, monitor, improve, or predict students’ learning processes using data about their learning activities captured in technology-mediated information systems (IS). Although EPM has recently attracted considerable research interest, there is still limited shared knowledge about the distinctive design characteristics of EPM from an integrative perspective. To address this gap, we conducted a systematic literature review to identify EPM characteristics. Building on a technology-mediated learning perspective, we develop a taxonomy that classifies EPM characteristics into four major categories (i.e., purpose, user, input, analysis). We evaluate and refine our taxonomy with ten domain experts, identified three clusters in the reviewed literature, and derived six archetypes of EPM scenarios based on our categorization. Finally, we formulate a novel research agenda to guide researchers in systematizing and synthesizing research on different technological embeddings of EPM in a students’ learning process.

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Behavioral experiments are a highly suitable method for testing theories, as they can establish causality while controlling for other confounding factors. However, researchers that aim to conduct and publish such studies face various concerns about the methodological approach. A lack of clarity exists in our field as to which related practices and design decisions are legitimate and accepted. To address this issue, we present a structured literature review that analyzes the designs of 168 behavioral experiments published in the Senior Scholars’ Basket of journals. We find that most experiments are confirmatory, individual-level, between-subjects laboratory experiments. At the same time, we find that some under-represented experiment designs, such as exploratory online experiments, may bear potential for identifying new behaviors and constructing new or proper-to-IS theories. This paper contains an in-depth discussion on the findings and provides decision support to IS researchers that seek to design and publish behavioral experiments.

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The role of the Chief Information Officer (CIO) in the organization has received a lot of attention in recent years. While traditionally most CIOs had faced the difficulty of stepping out of the shadow of being coined as a "Utility & Infrastructure Director", they have been found to establish themselves as a driving force in defining and shaping the digital agenda and strategic direction of their organization (Peppard et al. 2011). This crisis-driven development is, however, now paving the way for a new era of the CIO role. As research shows, crises usually do not lead to a trend reversal, but to a trend acceleration (Gassmann and Ferrandina 2021). Therefore, this opportunity should be seized by CIOs in order to leverage the digitalization momentum gained through the COVID-19 crisis, and to build lean digital organizational structures and use strategic sourcing of services for cost efficiency. Thus, the focus here should not be on rebuilding old barriers, but to use the crisis induced dynamic to empower the CIO to successfully master the future challenges of efficiency, flexibility, resilience, scalability and innovation in the organization.

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Since the emergence of conversational agents, this technology has seen continuous development and research. Today, advanced conversational agents are virtually omnipresent in our everyday lives. Albeit the numerous improvements in their conversational capabilities, breakdowns are still a persistent issue. Such breakdowns can result in a very unpleasant experience for users and impair the future success of conversational agents. This issue has been acknowledged by many researchers recently. However, the research on strategies to overcome conversational breakdowns is still inconclusive, and further research is needed. Therefore, we conduct a systematic literature analysis to derive conceptual conversational breakdown recovery strategies from literature and highlight future research avenues to address potential gaps. Thus, we contribute to theory of human-agent interaction by deriving and assessing recovery strategies and suggesting leads for novel recovery strategies.

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Voice assistants are a novel class of information systems that fundamentally change human–computer interaction. Although these assistants are widespread, the utilization of these information systems is oftentimes only considered on a surface level by individuals. In addition, prior research has focused predominantly on initial use instead of looking deeper into post-adoption and habit formation. In consequence, this paper reviews how the notion of habit has been conceptualized in relation to biographical utilization of voice assistants and presents findings based on a qualitative study approach. From a perspective of post-adoption users, the study suggests that existing habits persist, and new habits hardly ever form in the context of voice assistant utilization. This paper outlines four key factors that help explain voice assistant utilization behavior and furthermore provides practical implications that help to ensure continued voice assistant use in the future.

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The internet of things (IoT) and digital platforms have offered industrial companies new opportunities to compete against digital platform-native companies. To succeed in this competition, industry incumbents must learn to extend their traditional product and service business through platforms. However, extant research has focused primarily on the ability of platform owners to govern mature platforms for innovation but has largely ignored how industry incumbents can build these capabilities internally during the establishment of their platform ecosystems as part of larger transformational journeys. To address this gap, we conduct a multiple case study of three incumbent organizations, drawing on a dynamic capability lens. We identify 11 practical microfoundations of sensing, seizing, and reconfiguring dynamic capabilities that aided three incumbents in establishing their IoT platform ecosystems. Besides the transformational activities, our findings contribute to the literature on platform establishment through three IoT-related shifts that deviate from known digital platform paradigms.

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Design science research (DSR) aims to generate knowledge about innovative solutions to real-world problems. A comparably new stream of research, DSR has matured methodically, and is increasingly catching the interest of researchers, specifically for its potential to contribute to problem solving in society and the economy. Since research methodology curricula develop slowly, however, DSR is still underrepresented in most curricula and courses on research design and methods, and we lack guidance on what and how to teach in a DSR course in a way that enables junior academics to conduct DSR according to high standards. We report on teaching DSR methodology both on PhD and Master levels and for both managerially and technically oriented student populations. Our interactive on-site and distance formats have been refined over 14 years. The PDW presents an effective syllabus, teaching material and experience from conducting over 25 courses with students from over 20 countries across all three geographic AIS regions.

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Driven by economic advantages and the idea of disintermediation of business processes, the decentralization of technical and economic systems has become a highly discussed topic in recent years. Extant research primarily investigated the technical implementations of decentralized information systems (IS) and their use by firms in business networks. It became clear that interorganizational relationships and business functions must be transformed to enable the use of decentralized IS (e.g., those related to how firms can be involved in the design, instantiation, operation, and governance of decentralized IS). However, the impact of transforming business functions of individual firms remains largely unclear, obfuscating a comprehensive understanding of the implication of decentralized IS use on internal organizational structures of firms. In this work, we focus on the identification of challenges for firms in using distributed ledger technology (DLT as a representative for decentralized IS) and their effects on the business functions of firms.

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Facilitated by Artificial Intelligence technology, cognitive automation means to front and back offices what the pervasive automation through physical machinery and robots meant to production plants. Thus, we can automate tasks and processes that were unimaginable to be automated one decade ago. However, organizational adoption of cognitive automation is way below its possibilities, as this novel class of automation technology is perceived to be risky by organizations. This demands structured approaches for assessing the suitability of use cases for cognitive automation. Following the Design Science Research paradigm, we develop a method for assessing cognitive automation use cases. This enables practitioners to make more informed decisions on selecting, specifying, and embedding cognitive automation use cases in their organizations. For researchers, the method serves as a conceptual frame, which they can adapt to guide their empirical research or to use it for developing future decision support to shape the future of work.

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