The evolution of information systems (IS) in recent years, driven by advancements such as AI-based digital assistants and autonomous vehicles, has fundamentally changed human-IS interaction. This transformation extends beyond mere user interaction to encompass the emergence of agentic IS, challenging traditional notions of human supervision. It prompts a reevaluation of IS research, with a focus on IS delegation as a new theoretical lens. However, research remains nascent, particularly in understanding the factors influencing delegation decisions. We compiled 26 articles and derived six key delegation mechanisms and their influencing factors, using grounded theory and co-occurrence analysis. We investigate attributes of human and the agentic IS, as well as task attributes and the delegation level that are relevant to the delegation mechanisms. Our research provides a nuanced understanding of factors influencing delegation decisions to agentic IS. We call for research considering the yet underrepresented but crucial interdependencies with a research agenda.

Single organizations encounter intricate challenges in meeting the UN’s Sustainable Development Goals (SDGs) on their own and thus are increasingly concerned with forming ecosystems. This is also the case in the e-commerce domain. It is assumed that particularly focal actors of such ecosystems have the power to foster initiatives towards more sustainability. We conducted an embedded multi-case study with 135 initiatives collected from three types of e-commerce ecosystems to uncover what sustainability goals are addressed by different ecosystem participants. This paper’s analysis explores (1) what sustainability initiatives are reported from focal actors and differences depending on a specific type of ecosystem, (2) dependencies between SDGs within the initiatives, and (3) the degree of involvement of other ecosystem actors and how they contribute to certain SDGs. Our work synthesizes existing initiatives towards sustainable development to give orientation and impulses for practice and academia as well as outlines avenues for future research at the intersection of ecosystems and sustainability.

Online reinforcement learning (RL) is increasingly used for realizing adaptive systems in the presence of design time uncertainty because Online RL can leverage data only available at run time. With Deep RL gaining interest, the learned knowledge is no longer represented explicitly but hidden in the parameterization of the underlying artificial neural network. For a human, it thus becomes practically impossible to understand the decision-making of Deep RL, which makes it difficult for (1) software engineers to perform debugging, (2) system providers to comply with relevant legal frameworks, and (3) system users to build trust. The explainable RL technique XRL-DINE, introduced in earlier work, provides insights into why certain decisions were made at important time steps. Here, we perform an empirical user study concerning XRL-DINE involving 73 software engineers split into treatment and control groups. The treatment group is given access to XRL-DINE, while the control group is not. We analyze (1) the participants’ performance in answering concrete questions related to the decision-making of Deep RL, (2) the participants’ self-assessed confidence in giving the right answers, (3) the perceived usefulness and ease of use of XRL-DINE, and (4) the concrete usage of the XRL-DINE dashboard.

Die Bau- und Handwerksbranche zeigt seit Jahren eine verhältnismäßig niedrige Produktivitätssteigerung, verbunden mit einem geringen Digitalisierungsgrad. Angesichts von Mitarbeiterknappheit, zunehmender Komplexität von Bauprojekten und steigenden Individualisierungsanforderungen der Endkunden scheint die Digitalisierung einer der Schlüsselfaktoren zur Verbesserung der Produktivität zu sein. Der vorliegende Beitrag analysiert aus zwei strategischen Perspektiven die sich abzeichnenden Entwicklungen in dieser Branche: eine, die bestehende Wertschöpfungslogik und akteurszentrierte Sichtweise, und eine zukunftsweisende Perspektive auf plattformbasierte, service- und informationszentrierte Dienstleistungs-Ökosysteme. Die strategischen Perspektiven werden aus institutioneller Sichtweise eines Großhandelsbetriebs untersucht, welcher als zentraler Intermediär aufgrund zahlreicher Herausforderungen durch Disintermediation gefährdet ist. Die Re-Intermediation digitaler Plattformen und der Wandel hin zu serviceorientierten Geschäftsmodellen könnten disruptiv für die Leistungserstellung sein. Wenngleich eine solche Transition neue Wertschöpfungsansätze verspricht, ergeben sich für innovative Koordinations‑, Kommunikations- und Integrationskonzepte neue Herausforderungen. Basierend auf der strategischen Analyse werden die zentralen Herausforderungen, welche die mangelnde Etablierung der Technologisierung in der Bau- und Handwerksbranche zum Teil bedingen, exemplarisch anhand der Abbildung von Variantenartikeln im Stammdatenmanagement und der Auftragserfassung analysiert. Die zunehmende Variantenvielfalt in der Bau- und Handwerksbranche kann stammdatenseitig über konfigurierbare Materialien abgebildet werden. Diese Materialart bietet für Vertriebsmitarbeiter und Kunden eine Variantenkonfiguration anhand vorab definierter Merkmale. In der Belegerfassung sind zukünftig vielfältige Geschäftsvorfälle und Kundentypen zu integrieren, um das Tagesgeschäft im Vertrieb bestmöglich zu unterstützen. Die skizzierten Herausforderungen müssen durch Standardisierung und intelligente IT-Systeme bzw. Stammdatenkonzepte gelöst werden, um die konstatierten Produktivitätsdefizite überwinden zu können und die Digitalisierung der Bauhandwerker zu stärken.

The construction and crafts sector has seen a relatively low increase in productivity for years, combined with a low level of digitalization. In light of labor shortages, the increasing complexity of construction projects, and rising demands for customization from end customers, digitalization appears to be a key factor in enhancing productivity. We analyze the emerging developments in this sector taking two strategic perspectives: one that preserves existing value creation logic and actor-centric views, and another that looks forward to platform-based, service- and information-centric business ecosystems. The strategic perspectives are explored from the institutional viewpoint of a wholesale business, which, as a central intermediary, faces potential threats from disintermediation. The re-intermediation through digital platforms and the shift towards service-oriented business models could be disruptive, transforming traditional value chains into network-like structures. While this transition promises new value creation approaches, it also poses fresh challenges for innovative coordination, communication, and integration concepts. Based on this strategic analysis, key challenges impeding the full adoption of technology in the construction and trades sector are examined, particularly through the lens of variant article representation in master data management and order processing. The increasing variety of construction materials can be managed through configurable materials in master data, allowing for predefined variant configurations by sales staff and customers. Future document processing must integrate diverse business transactions and customer types to support sales operations effectively. Addressing these challenges through standardization and advanced IT systems is essential for overcoming productivity deficits and enhancing digitalization in the trade sector.

Platform-based ecosystems dominate e-commerce, generating value through participant growth and resulting network effects. However, research has lacked any conceptualization of value creation in e-commerce ecosystems. This paper fills this gap by providing a theoretically grounded and empirically validated conceptualization of value creation and exchange, including roles, value creation activities, and value flows among participants. The model integrates insights from a systematic literature review and a multi-case study of ten leading e-commerce ecosystems. Furthermore, an extension to the e3-value notation is proposed by introducing ecosystem segments, allowing for a higher level of abstraction of meta-roles and individual ecosystem participants.

The tourism industry plays a crucial role in many countries and has suffered under the global events of the last years (e.g., COVID-19, economic recession) with a decline in visitors and economic contributions. Through digitalization efforts of cities and states, smart tourism destinations use emerging technologies like the Internet of Things and Smart Services to provide rich on-site experiences for visitors, hoping to increase their competitiveness and attract new tourists. By conducting a design science research project in collaboration with a German municipality, this paper aims to explore how digital assistants should be designed in the context of smart tourism. Based on expert interviews and a multi-case study of 37 tourism apps, we were able to develop twelve key design principles for smart tourism applications, evaluated through a prototypical instantiation, to create design knowledge for the digitalization of tourism.

E-commerce is one of the most important sectors of the economy, with an expected global turnover of USD 7.4 trillion in 2024. Leading companies in the industry like Amazon and Alibaba leverage platform business models that orchestrate complex ecosystems of buyers and sellers. These ecosystems are characterized by globally intertwined networks of independent participants and multifaceted interactions, making their development hard to predict. We propose an agent-based simulation approach, following the three-step process of Haki et al. (2020), to predict the behavior of e-commerce ecosystems with a particular focus on the impact of premium subscription services. Simulation models offer the opportunity to tangibly visualize the effects of a participant's actions on the ecosystem level. Our simulation includes the key actors (i.e., buyer, seller, marketplace), their characteristics, and behaviors to draw conclusions about the evolution of the ecosystem and the strategic role of premium memberships in shaping these digital landscapes.

Car manufacturers and suppliers in the Automotive industry increasingly face the issue of optimization of highly complex supply chains that need to accommodate each customer's precise demands, requiring a vast array of parts and information to be available at the right place and at the right time. This involves data sharing between organizations, which is hindered by various issues, such as fear of data misappropriation by the data receiver or the involuntary disclosure of business secrets. The paper proposes design principles for a novel type of Inter-Organizational Information System, which addresses these challenges through the technical implementation of data sovereignty. The study reports on an Action Design Research study in the Automotive industry between a car manufacturer and a 1st-tier supplier. It contributes (a) design requirements, (b) design features, (c) an instantiation, and (d) design principles for this type of data sovereign inter-organizational information system.

Digital communication has become an essential part of both personal and professional contexts. However, unique characteristics of digital communication—such as lacking non-verbal cues or time asynchrony—clearly distinguish this new form of communication from traditional face-to-face communication. These differences raise questions about the transferability of previous findings on traditional communication to the digital communication context and emphasize the need for specialized research. To support and guide research on the analysis of digital communication, we conducted a systematic literature review encompassing 84 publications on digital communication in leading journals. By doing so, we provide an overview of the current body of research. Thereby, we focus on distinct fields of communication, methods used to collect and analyze digital communication data, as well as common methodological limitations. Building on these insights, we derive a series of comprehensive guidelines from five distinct areas for the collection and analysis of digital communication that can guide future research and organizational practice.

Massive open online courses (MOOCs) have significantly transformed e-learning by providing global accessibility, collaborative learning opportunities, and high-quality educational content. However, MOOCs face limitations such as limited social interaction, delayed feedback, and linguistic barriers. To overcome these challenges, there is a growing interest in research to leverage artificial intelligence (AI) technologies. In this study, we conduct a systematic literature review examining the capabilities of generative AI (GenAI) and its implications for e-learning in MOOCs. We identify ten capabilities of GenAI, including analytical processing, generative, (personalized) assistant, support, feedback, assessment, communication, reflection, adaptivity, and accessibility. The findings highlight GenAI’s potential to overcome challenges in MOOCs by providing insightful and contextually relevant responses, generating new content, facilitating multilingual interactions, and enhancing the overall e-learning experience. We therefore contribute to the broader understanding of GenAI’s impact on e-learning and suggest avenues for future research on GenAI and its integration in MOOCs.

As global challenges, such as pandemics, population growth and widespread illnesses, continue to rise, healthcare systems are facing greater strain, resulting in a shortage of resources and increased demands for medical care. Effective communication between healthcare professionals and patients is essential for the provision of good services to prevent confusion and induced anxiety of patients, particularly when medical jargon is employed and not understood. Generative AI (GAI) presents a chance to transform healthcare communication by providing language processing capabilities that enhance patient-centered services. This paper examines how GAI-based conversational agents for explaining medical jargon in healthcare should be designed. We derived eleven design principles from a systematic literature review and evaluated them with nine clinical cardiological scenarios through a prototypical instantiation of an LLM-based conversational agent. The results provide insights for researchers and healthcare providers in form of prescriptive design knowledge to improve patient communication using GAI.

Der Forschungsbereich der digitalisierten Produkte (engl. smart products) ist vergleichsweise als jung und innovativ einzuordnen, weshalb die Forschung in dem Bereich bisher sehr heterogen und wenig holistisch ist und sich zudem auf etliche unterschiedliche Domänen verteilt. Als Folge fehlen zum einen oftmals fundierte Lösungen und zum anderen werden zahlreiche Herausforderungen in der Praxis nicht von der Forschung aufgegriffen. Erschwert wird die Situation zusätzlich einerseits durch eine fehlende einheitliche Terminologie und andererseits durch die immer häufiger stattfindende Erweiterung von digitalisierten Produkten zu umfangreichen Ökosystemen.

Das Ziel der vorliegenden Arbeit war daher die Konsolidierung des bisherigen Wissens über die Entwicklung digitalisierter Produkte aus den verschiedenen Anwendungs- und Forschungsdomänen zur Etablierung eines einheitlichen Body of Knowledges für die Forschung. Hierfür wurde ein domänenübergreifendes Reifegradmodell entwickelt und evaluiert, das Unternehmen bei der komplexen und von verschiedenen Herausforderungen tangierten Umsetzung unterschiedlicher Entwicklungsstufen der digitalisierten Produkte (z. B. Einzelprodukt, Produktsystem, System-of-Systems) unterstützt.

Durch das entwickelte, rasterbasierte Stufenmodell erhalten Unternehmen einerseits die Möglichkeit der Ist-Zustandsbewertung der im Unternehmen entwickelten digitalisierten Produkte und andererseits Zielvorgaben in Abhängigkeit zu der (zukünftig) angestrebten Produktentwicklungsstufe. Die Zielvorgaben decken dabei alle von der Entwicklung betroffenen Unternehmensbereiche ab, wie z. B. die Unternehmensstrategie, die Investitions- und Finanzierungsmöglichkeiten, die Unternehmensstruktur, die Unternehmensprozesse, die IT-Architektur oder das Stakeholder Management.

Die Entwicklung und Evaluation des Modells zeigte darüber hinaus sowohl Weiterentwicklungsmöglichkeiten des Modells als auch Ansätze zur Verbesserung der Reifegradmodellentwicklung im Allgemeinen auf. Dadurch konnte ein Beitrag zur Praxis und Forschung geleistet werden.

Research on smart products is still a young and innovative area of interest resulting in a heterogeneous and fragmented research field with many varying domains. Thus, well-grounded and comprehensive support for e.g., the development is often not available, while at the same time numerous challenges in practices and research are present. A missing consistent terminology and the advancement of smart products to large ecosystems complicates the situation even further.

Therefore, the goal of this research thesis was the consolidation of existing knowledge of different application and research areas about the development of smart products into a consistent body of knowledge. For this purpose, a research and application domain overarching maturity model was drafted, developed and evaluated. The model should support organizations with the complex and challenging development of different product maturity stages of smart products (e.g., smart product, product system, system-of-systems).

The resulting grid model allows for an (descriptive) as-is state assessment of the organizational smart products and provides the model users with improvement objectives in relation to the targeted product maturity stage. The objectives concern all organizational levels e.g., the strategy development, financial planning, organizational structure, organizational processes, IT architecture or stakeholder management.
Moreover, the model development and evaluation demonstrated potential for fur ther improvement of the developed model as well as the overall maturity model research. In doing so, contribution to practice and research of smart products and maturity model development in general could be achieved.

The price is the most important determinant for product sales and is highly influential for a company's success. Nevertheless, price determination often follows individuals’ rules of thumb augmented with product and economic performance indicators. With the increasing dissemination of artificial intelligence in organizations and society, the accuracy of price determination in retail might be

enhanced by sophisticated pricing algorithms. Technological developments further increase the number of pricing algorithms and pricing tools available. Against this backdrop, we applied Nickerson et al.’s (2013) approach, proposing a taxonomy for describing pricing algorithms in retail. The taxonomy

consists of 19 dimensions and 59 characteristics. Analyzing 70 pricing tools revealed a high specialization for selected retail domains, a focus on competitor monitoring and dynamic pricing, and a minor use of current machine learning techniques. This is a first attempt at structuring pricing algorithms and developing a price management toolbox that constructs artificial intelligence-enabled pricing algorithms.

This study examines the effects of integrating a technically advanced and more human-like large language model into a voice assistant to assess, how technical advancements mitigate user annoyances. Therefore, a generative pre-trained transformer was integrated into Siri and made available to 23 interview participants. Preliminary results reveal a decrease in user-reported annoyances, showing that the integration not only improves technical accuracy but also enhances the perceived humanness of interactions. However, subsequent interviews indicated that the distinction between the effects of technical advancements and the infusion of humanness emerged as critical, indicating a complex interplay between these factors. It is therefore planned to differentiate between technical and human improvements in the further development of this article. The results contribute to the discourse on optimizing voice assistants by pinpointing the reduction of user annoyances as a pivotal factor in improving user experience, suggesting pathways for future enhancements in voice assistant platforms.

Collaboration and value co-creation are important drivers of the continuous growth of e-commerce, which is expected to reach US \$6.4 trillion in 2024 despite current global crises. Only a few transaction platforms currently dominate e-commerce (eg., Amazon, Walmart), but other participants are likely to join these platforms’ ecosystems. Third-party developers can provide extensions to these ecosystems to enhance the platforms’ functionality, but third-party developers’ role in e-commerce ecosystems’ success and generativity remains underexamined in academia. The present study scrutinizes the efficacy of boundary resources in attracting and managing third-party developers in e-commerce ecosystems. This investigation is predicated upon qualitative data gathered through interviews with 14 domain experts. The insights derived from these interviews have culminated in the formulation of seven design principles. These design principles are envisaged to serve as a guiding framework for owners of innovation and transaction platforms within the e-commerce sphere, facilitating the strategic deployment of boundary resources. It is anticipated that collaboration, value creation, and the overall generative capacity as well as the success of e-commerce ecosystems shall be considerably enhanced.

\\\{Labeling is critical in creating training datasets for supervised machine learning, and is a common form of crowd work heteromation. It typically requires manual labor, is badly compensated and not infrequently bores the workers involved. Although task variety is known to drive human autonomy and intrinsic motivation, there is little research in this regard in the labeling context. Against this backdrop, we manipulate the presentation sequence of a labeling task in an online experiment and use the theoretical lens of self-determination theory to explain psychological work outcomes and work performance. We rely on 176 crowd workers contributing with group comparisons between three presentation sequences (by label, by image, random) and a mediation path analysis along the phenomena studied. Surprising among our key findings is that the task variety when sorting by label is perceived higher than when sorting by image and the random group. Naturally, one would assume that the random group would be perceived as most varied. We choose a visual metaphor to explain this phenomenon, whereas paintings offer a structured presentation of coloured pixels, as opposed to random noise.}

Object-oriented modeling languages provide various concepts to express abstractions, which foster reuse and integrity. Among these concepts, generalization/specialization is of specific relevance. However, in many cases where generalization/specialization seems to be a natural choice, its use is likely to jeopardize a system’s integrity. Delegation has for long been known as an alternative that allows preventing the accidental damage caused by the inproper use of specialization. Nevertheless, delegation is ignored by most tools for object-oriented modeling as well as by many textbooks, which may be caused by the fact that there is no unified conception of delegation, and that delegation is not supported by most object-oriented programming languages. This paper aims at a revival of delegation. To that end, the need for delegation is motivated by the analysis of counter-intuitive effects of specialization. Based on an extensive requirements analysis, a new, extended conception of delegation is presented. It allows for using delegation between classes on any (meta-) level and introduces the "delegation to class" pattern. Delegation in multi-level environments enables an additional reduction of redundancy and, hence, promotes integrity. The paper also presents design guidelines to foster the appropriate use of delegation. With respect to the implementation of delegation with object-oriented programming languages, two alternative flavours of delegation are analyzed. Finally, a prototypical implementation within a language engineering and execution environment does not only demonstrate the use of delegation in a modeling tool, but also its seamless implementation, by featuring a common representation of models and code at runtime.

How do new entrepreneurial ventures effectively deploy linguistic frames to attract customer demand? Drawing on framing and categories research, we develop and test theory about how category dynamics shape the effectiveness of two commonly observed frames—social impact framing and innovativeness framing—in the context of prosocial categories. We test our predictions by tracking entrepreneurial ventures in the market category for massive open online courses over the category's first 10 years of existence (2012–2021). Our fixed-effects models show that higher levels of category salience increase the effectiveness of a social impact framing but decrease the effectiveness of an innovativeness framing; conversely, higher levels of category crowdedness decrease the effectiveness of a social impact framing but increase the effectiveness of an innovativeness framing.

Generative Artificial Intelligence (GAI) is a prevalent topic in recent research and business, seemingly taking the position of a disruptive technology that has the potential to significantly transform industries ranging from productivity (e.g., ChatGPT-4) to creativity (e.g., DALL-E). While the emerging scientific discussion on GAI covers a variety of fields and issues, such as privacy, accuracy, and application scenarios, this paper sheds light on the business side of GAI by investigating the morphologic nature of start-ups and incumbents leveraging GAI. Based on the structured analysis of 100 real-world instances, we report on a taxonomy of GAI applications and services that advances our practical understanding, strengthens the distinguishability, as well as adds clarity to the discourse of GAI potentials. We provide an initial framework and five types of GAI, namely Generator, Reimaginator, Synthesizer, Assistant, and Enabler, that are informed by the core characteristics of the technology paradigm.

The diffusion of AI-technology disrupts labor and industries and gives rise to a diverse range of new ventures and product innovations. Such product innovations involve the negotiation of product boundaries among actors in innovation networks, including ventures, investors, and customers. These negotiations consist of social and cognitive translations. For digital products, actors share a common understanding of resource configuration, mainly based on cognitive resonance. However, AI-driven products introduce the “black-box” problem that hinders cognitive translation-based negotiations within innovation networks, as they are not fully cognitively traceable, but emotionally resonant. Using a qualitative research approach and the notion of entrepreneurial framing, we investigate the impact of AI on the negotiation of product boundaries and digital innovation. We reveal that AI-ventures, to maintain ”cognitive” superiority, focus on cutting-edge technology while limiting negotiation to non-technology aspects, such as revenue streams and business models, creating ”cognitive moats” for non-expert actors.

Recent developments in the field of artificial intelligence (AI) have enabled new paradigms of machine processing, shifting from data-driven, discriminative AI tasks toward sophisticated, creative tasks through generative AI. Leveraging deep generative models, generative AI is capable of producing novel and realistic content across a broad spectrum (e.g., texts, images, or programming code) for various domains based on basic user prompts. In this article, we offer a comprehensive overview of the fundamentals of generative AI with its underpinning concepts and prospects. We provide a conceptual introduction to relevant terms and techniques, outline the inherent properties that constitute generative AI, and elaborate on the potentials and challenges. We underline the necessity for researchers and practitioners to comprehend the distinctive characteristics of generative artificial intelligence in order to harness its potential while mitigating its risks and to contribute to a principal understanding.

The increasing online competition, associated changes in customer behaviors, and effects of the pandemic in recent years have led to increasing retail store closures. This development has given rise to a downward spiral in terms of a decreasing attractiveness of local shopping places and a further reduction of stores. Research has recognized that smart services can unleash the potential to compensate for the competitive disadvantages of physical retailers by combining tailored physical and digital offerings to enhance customer-oriented value creation. However, most approaches are limited to in-store services without addressing the wider shopping experience in retail surroundings. Therefore, this paper provides a classification framework for smart services in retail evaluated against 163 use cases, as well as six service archetypes. This work contributes to understanding relevant service design elements and proposes applying the idea of a holistic customer experience to service design in physical retail environments.

Background: Online pharmacies are used less than other e-commerce sites in Germany. Shopping behavior does not correspond to consumption behavior, as online purchases are predominantly made for over-the-counter (OTC) medications. Objective: The objective of this study was to understand the purchasing experiences of online pharmacy customers in terms of critical factors for online pharmacy adoption. Methods: This study examined the perceived risk, perceived trust, and emotions related to purchasing medications online and, consequently, the purchase intention toward online pharmacies. In a within-subjects design (N=37 participants), 2 German online pharmacies with different perceptions of risk and trust were investigated for their main business, namely OTC and prescription drugs. The results of a preliminary study led to 1 online pharmacy with high and 1 with significantly low self-reported risk by the prestudy sample. Emotions were measured with a multimethod approach during and after the purchase situation as follows: (1) neural evaluation processes using functional near-infrared spectroscopy, (2) the automated direct motor response during the use of the online pharmacy via facial expression analysis (FaceReader), and (3) subjective evaluations through self-reports. Following the shopping experiences at both pharmacies for both product types, risk, trust, and purchase intention toward the pharmacies were assessed using self-assessments. Results: The 2 online pharmacies were rated differently in terms of risk, trust, emotions, and purchase intention. The high-risk pharmacy was also perceived as having lower trust and vice versa. Significantly stronger negative emotional expressions on customers' faces and different neural activations in the ventromedial prefrontal cortex and dorsomedial prefrontal cortex were measured when purchasing prescription drugs from the high-risk pharmacy than from the low-risk pharmacy, combined with OTC medications. In line with this, customers' self-ratings indicated higher negative emotions for the high-risk pharmacy and lower negative emotions for the low-risk pharmacy. Moreover, the ratings showed lower purchase intention for the high-risk pharmacy. Conclusions: Using multimethod measurements, we showed that the preceding neural activation and subsequent verbal evaluation of online pharmacies are reflected in the customers' immediate emotional facial expressions. High-risk online pharmacies and prescription drugs lead to stronger negative emotional facial expressions and trigger neural evaluation processes that imply perceived loss. Low-risk online pharmacies and OTC medications lead to weaker negative emotional facial expressions and trigger neural evaluation processes that signify certainty and perceived reward. The results may provide an explanation for why OTC medications are purchased online more frequently than prescription medications.

In Explainable Artificial Intelligence (XAI) research, various local model-agnostic methods have been proposed to explain individual predictions to users in order to increase the transparency of the underlying Artificial Intelligence (AI) systems. However, the user perspective has received less attention in XAI research, leading to a (1) lack of involvement of users in the design process of local model-agnostic explanations representations and (2) a limited understanding of how users visually attend them. Against this backdrop, we refined representations of local explanations from four well-established model-agnostic XAI methods in an iterative design process with users. Moreover, we evaluated the refined explanation representations in a laboratory experiment using eye-tracking technology as well as self-reports and interviews. Our results show that users do not necessarily prefer simple explanations and that their individual characteristics, such as gender and previous experience with AI systems, strongly influence their preferences. In addition, users find that some explanations are only useful in certain scenarios making the selection of an appropriate explanation highly dependent on context. With our work, we contribute to ongoing research to improve transparency in AI.

Although our digitalized society is able to foster social inclusion and integration, there are still numerous communities having unequal opportunities. This is also the case with deaf people. About 750,000 deaf people only in the European Union and over 4 million people in the United States face daily challenges in terms of communication and participation, such as in leisure activities but more importantly in emergencies too. To provide equal environments and allow people with hearing handicaps to communicate in their native language, this paper presents an AI-based sign language translator. We adopted a transformer neural network capable of analyzing over 500 data points from a person’s gestures and face to translate sign language into text. We have designed a machine learning pipeline that enables the translator to evolve, build new datasets, and train sign language recognition models. As proof of concept, we instantiated a sign language interpreter for an emergency call with over 200 phrases. The overall goal is to support people with hearing inabilities by enabling them to participate in economic, social, political, and cultural life.

The increasing online competition, associated changes in customer behaviors, and effects of the pandemic in recent years have led to increasing retail store closures. This development has given rise to a downward spiral in terms of a decreasing attractiveness of local shopping places and a further reduction of stores. Research has recognized that smart services can unleash the potential to compensate for the competitive disadvantages of physical retailers by combining tailored physical and digital offerings to enhance customer-oriented value creation. However, most approaches are limited to in-store services without addressing the wider shopping experience in retail surroundings. Therefore, this paper provides a classification framework for smart services in retail evaluated against 163 use cases, as well as six service archetypes. This work contributes to understanding relevant service design elements and proposes applying the idea of a holistic customer experience to service design in physical retail environments.

The appropriate selection of suitable process models plays an important role for IT project success. To aid in decision-making, IT project management literature offers a plethora of decision models for selecting suitable process models, however, hybrid process models are often neglected and adoption in practice is low or non-existent. To address this challenge, we draw on contingency theory to develop and implement a tool-supported decision model for the selection and evaluation of appropriate process models for IT projects, thereby leveraging artificial intelligence and machine learning in the context of a self-enforcing network. Our model provides an objective tool to assess process model suitability. Results from a conducted online survey with project management experts indicate high validity. Therefore, we contribute to the field of IT project management by expanding AI-based decision models for selecting and evaluating process models through extending the range of covered models and implementing inherent weighting of criteria.

The role of artificial intelligence in daily life is constantly advancing and has become an important topic of discussion. With music and its lyrics being a vehicle to express topics of society, this paper investigates how artificial intelligence is perceived by musicians and reflected in their songs. By analyzing the lyrics of over 1,200 songs over three decades, this work applies sentiment analysis to extract polarities and emotions. The results provide insights into how musicians view and reflect the impact of artificial intelligence on society and how this is reflected in their song texts. The findings show an increase in songs mentioning artificial intelligence-related terms, with a trend of more songs implying negativity, such as anger. However, minor increases in positive emotions indicate musicians' ambivalent views on hopes and fear of artificial intelligence.

Abstract
In this paper we present a long-term research project that started in 2011. Language Engineering for
Multi-Level Modeling (LE4MM) combines research on fundamental challenges of conceptual modeling
and software engineering with the design and implementation of a tool environment. This interplay
between research and development has proved very fruitful. Notwithstanding, running a research project
over a period of more than 10 years, especially when it involves software development, faces a number
of specific challenges. While the main focus of the paper is on research questions and findings, we will
also present lessons learned in the project

The modern world is confronted with grand challenges, such as those codified by the United Nations’ Sustainable Development Goals. As single organizations are often not capable of addressing a broad set of goals on their own, they are increasingly concerned with creating ecosystems. This is also the case in the domain of e-commerce. Owners of focal platforms in e-commerce ecosystems have the power to implement sustainability initiatives and therefore need to be equipped with an overview of possible initiatives and actionable guidance. To unbox how e-commerce ecosystem participants consider sustainability, we conducted a multi-case study with 99 initiatives collected from sustainability reports. We found that (1) sustainability initiatives particularly focus on reducing inequality and managing climate change as well as (2) manufacturers, sellers, and service providers are the most involved ecosystem participants. Based on our findings, we (3) synthesized six categories of sustainability initiatives as measurements.

Machine learning (ML) has the potential to take on a variety of routine and non-routine tasks in brick-and-mortar retail and e-commerce. Many tasks previously executed manually are amenable to computerization using ML. Although procedure models for the introduction of ML across industries exist, the tasks for which ML can be implemented in retail need to be determined. To identify these application areas, we followed a dual approach. First, we conducted a structured literature review of 225 research papers to identify possible ML application areas in retail, as well as develop the structure of a well-established information systems architecture. Second, we triangulated these preliminary application areas with the analysis of eight expert interviews. In total, we identified 21 application areas for ML in online and offline retail; these application areas mainly address decision-oriented and economic-operative tasks. We organized the application areas in a framework for practitioners and researchers to determine appropriate ML use in retail. As our interviewees provided information at the process level, we also explored the application of ML in two exemplary retail processes. Our analysis further reveals that, while ML applications in offline retail focus on the retail articles, in e-commerce the customer is central to the application areas of ML.

The identification and satisfaction of user needs in business-to-consumer ecommerce is crucial to elicit positive experiences and establish loyalty toward the business. One major interface to the consumer is the website of the business, which can impact the user and customer experience throughout the whole journey. Current approaches that aim to measure user experience (UX) and related constructs have significant shortcomings and are often not able to uncover spontaneous processes in website users. Related neuroIS research proposes that a great part of behavior is formed by these spontaneous processes and that the utilization of additional, neurophysiological measurements can help to uncover these processes and better understand user behavior. Therefore, and to address the shortcomings of common UX measurements in ecommerce, this cumulative thesis presents 6 essays along different UX phases being pre-use, during-use, and post-/repeated-use of the ecommerce website. As a means to assess the spontaneous, potentially unconscious processes, the neuroimaging method fNIRS is utilized in the included essays. Across all papers, several responses to website design factors across UX phases could be identified on the neural level. The complementing self-reported data could reveal these effects only to a certain degree. Consequently, this thesis shows the contribution of neuroimaging (fNIRS) to UX investigation on ecommerce websites to better understand users, which helps to optimize website design and thus, UX.

The assumption that generativity engenders unbounded growth has acquired an almost taken-for-granted position in information systems and management literature. Against this premise, we examine the relationship between generativity and user base growth in the context of a digital platform. To do this, we synthesize the literature on generativity into two views, social interaction (expansion of ecosystem boundaries) and product view (expansion of product boundaries), that jointly and individually relate to user base growth. Both views help us explain how opening a platform relates to the emergence and resolution of conflicting expectations in a platform ecosystem that result in new functions and expanded use. We adopt a panel vector autoregressive approach combining data from six large transaction platforms that engaged with open-source developer communities. We found that the dominant narrative of generativity engendering growth, although generally supported by our analysis, obscures the fact that the inverse is also true; that is, growth can lead to expansion of product boundaries (inverse generativity) and that generativity can be bounded; that is, growth can stabilize ecosystem boundaries (bounded generativity). Against this background, we propose an extended generativity theory that presents generativity and growth in an integrative view and raises awareness about the limitations of the “unbounded growth” claim. We conclude that there is value in separating the two views of generativity conceptually and analytically, along with their relationship to user base growth, and we call for research on the pathways through which generativity produces growth.History: Ola Henfridsson, Senior Editor; Robert Wayne Gregory, Associate Editor.Supplemental Material: The online appendix is available at doi.org/10.1287/isre.2023.1209.

The turmoil of the COVID-19 pandemic caused organizations to transform their operations on a massive scale, with many responding by increasing the use of digi- tal technologies and digitally transforming themselves. However, these crisis-driven digital transformations happened under new and unknown conditions. In this article, we identify crisis-related challenges to established digital transformation "logics" and describe how small and medium-sized organizations in Germany (the "German Mittel-stand") responded to these challenges. Based on their experiences, we provide recommendations for successfully navigating crisis-driven digital transformations.

Manipulating their environment is one of the fundamental actions that humans, and actors more generally, perform. Yet, today’s mixed reality systems enable us to situate virtual content in the physical scene but fall short of expanding the visual illusion to believable environment manipulations. In this paper, we present the concept and system of Scene Responsiveness, the visual illusion that virtual actions affect the physical scene. Using co-aligned digital twins for coherence-preserving just-in-time virtualization of physical objects in the environment, Scene Responsiveness allows actors to seemingly manipulate physical objects as if they were virtual. Based on Scene Responsiveness, we propose two general types of end to-end illusionary experiences that ensure visuotactile consistency through the presented techniques of object elusiveness and object rephysicalization. We demonstrate how our Daydreaming illusion enables virtual characters to enter the scene through a physically closed door and vandalize the physical scene, or users to enchant and summon far-away physical objects. In a user evaluation of our Copperfield illusion, we found that Scene Responsiveness can be rendered so convincingly that it lends itself to magic tricks. We present our system architecture and conclude by discussing the implications of scene-responsive mixed reality for gaming and telepresence.

As the importance of machine learning (ML) in technology has increased over past years, it is important to understand each application and its implications for ML individually. As a sample application of ML, demand forecasts occupy a special position in industry and retail and are used in numerous optimization activities, such as price optimization. In past years, demand forecasting has transformed the way retailers and industry replenish their goods. From a manual process, forecast-driven replenishment processes are now used. While this process has very few requirements for the ML-based demand forecast, this changes when further processes are transformed. While optimizing prices, demand forecasting requires elasticity regarding optimization objectives. When ML methods are used for demand forecasting, there must be sufficient data to learn the proper elasticity requirements. To overcome the problem of missing historical data resulting in low elasticity and thus bad optimization performance, we present a method for transferring knowledge between articles and companies to train shared ML models. For the first time, we are able to optimize prices without generating historical demand data for all possible prices. Evaluations of a design science project show that federated learning with neural networks achieves good forecasting accuracy and high elasticity.

The financial sector is undergoing a massive transformation, with new technology-driven players challenging established mechanisms and transforming the sector into a fast-moving market. With the gradual transition from a scale economy to a platform-driven network economy, enterprise networks are gaining strategic importance. Despite the growing interest in fintech’s, research has so far lacked a conceptualization of value creation in fintech ecosystems. Therefore, this research paper aims to analyze key players, value creation activities, and value streams based on the analysis of the business models of payment services, personal financial management, robo-advisory, peer-to-peer lending, trading, and cryptocurrency. We present a holistic value network for the fintech ecosystem based on structured literature review and analysis of 171 fintech companies. We were able to show that fintech platform orchestrates multiple market sides and that customers take four distinct roles at the center of the ecosystem when using fintech services.

Theory is an essential part of design research and helps us to explain what we see or guide what we design. In the paper, we shed light on how kernel theories are used in developing design principles in Design Science Research (DSR). We do this by reporting on a systematic literature review, from which we have extracted a set of six mechanisms to operationalize kernel theory. Each mechanism consists of an activity (e.g., “transform to” or “derive from”) and an application point (e.g., meta-requirements or design principles) representing wherein the chain of concepts the kernel theory was used. The paper reflects on what we have learned about the use of kernel theories and translates this into recommendations and issues for further research. We provide researchers with guidance to use kernel theories more efficiently and give a big picture of the possibilities of kernel theory operationalization.

Multi-level modeling (MLM) facilitates the design of modeling languages because foundational language concepts (defined with “linguistic” metamodels) can be reused on any classification level and consequently frees the developer from the burden of re-specifying these concepts each time a new language is designed. This strength of MLM can be used profitably in teaching since it enables students to specify languages with relatively little effort with associated tool support. However, MLM introduces new features that require existing methods to be extended with user support and which introduce verification challenges. This paper describes these challenges with respect to teaching modeling languages and outlines approaches to address them.
 

A process of a multi-level model creation follows typically the topdown approach, i.e., it requires first defining concepts and relations on the highest classification levels, which only then can be used to create concepts on the lower ones. Empirical insights into the process of multi-level model creation suggest however, that this strategy may be counter-intuitive and challenging, especially for non-experts. This paper addresses this problem by focusing on the idea of flexible multi-level model creation, understood as an intertwined application of top-down and bottom-up strategies. As a first step towards realizing this vision for multi-level models in general, and those created with the XModeler and Flexible MetaModeling and Execution Language (FMMLx) in particular, in this paper, we select a set of relevant multi-level refactoring patterns, adapt them to our approach, and implement them in the supporting tool. We illustrate the flexible creation process using an exemplary scenario.
 

Die Entscheidungen im Marketingmix und besonders jene über Preis und Platzierung waren im Handel stets von enormer Bedeutung, aber bisher wenig automatisiert oder datengetrieben. Dies liegt darin begründet, dass es bisher keine Notwendigkeit dafür gab und ein Mangel an informationstechnischen Möglichkeiten limitierend wirkte. Aufgrund der zunehmenden Online-Affinität der Kunden und der dort nun schon seit einigen Jahren zu beobachtenden Preisvariationen hat sich dort ein anderes Preisgeschehen etabliert. Die vorgestellte Fallstudie zeigt auf, wie bisher nicht verfügbare Daten erfasst und genutzt werden können, um mit der Verknüpfung der Variablen Preis und Platzierung neuartige Entscheidungen zu treffen. Dennoch bleiben die Komplexität und Menge an Entscheidungen im Single-Channel-Handel auf wenige Entscheidungen begrenzt. Sobald nun aber mehrere Kanäle im Omni-Channel …

While standardized enterprise systems (ES) have become widely accepted, this is not the case for machine learning (ML) implementations, which are mostly developed individually in company-specific projects. Necessary historical data and rare ML capabilities result in a low cross-market ML utilization. To overcome the high usage barriers of ML, it should be incorporated into ES in a standardized manner. Therefore, we propose to implement an ML marketplace. While marketplaces in ES already exist, this paper proposes a marketplace dedicated to the exchange of ML models in a federated learning approach. Accordingly, this work formulates four meta requirements based on interviews, which are structured by marketplace governance dimensions. With these meta-requirements, an ML marketplace was implemented in a design science research project, from which eight design principles are derived. The design principles address governance dimensions for making ML accessible to many companies and allow them to integrate ML into existing ES.

This paper presents prototypical multi-level models of two uses cases. They comprise models of business processes and of models that represent the context required to execute a business process. On the one hand, the context consists of the organizational units that are responsible for the execution of processes. They are represented by a model of organizational structures. On the other hand, the context includes the artifacts that are needed or manipulated by processes. The models serve to demonstrate the specific power of multi-level modeling. First, they integrate models on higher levels, which correspond to domain-specific modeling languages, with those on lower levels. In addition, models are supplemented with objects on L0 to demonstrate how these can be integrated. The models are executable without the need to generate code, since models and corresponding program code share the same representation, thus demonstrating the possibility of advanced application system architectures, which allow users to navigate a comprehensive representation of the system they work with at runtime. The presentation of the models is supplemented with a general evaluation of multi-level concepts. The design of the models was inspired by the EMISA process challenge. Therefore, they are evaluated against the requirements defined with the challenge. In addition, a challenge is discussed that goes beyond the challenge, that is, the design of multi-level models of behavior.

Data processing systems operate in increasingly dynamic environments, such as in cloud or edge computing. In such environments, changes at run time can result in the dynamic appearance of data protection vulnerabilities, i.e., configurations in which an attacker could gain unauthorized access to confidential data. An autonomous system can mitigate such vulnerabilities by means of automated self-adaptations. If there are several data protection vulnerabilities at the same time, the system has to decide which ones to address first. In other areas of cybersecurity, risk-based approaches have proven useful for prioritizing where to focus efforts for increasing security. Traditionally, risk assessment is a manual and time-consuming process. On the other hand, addressing run-time risks requires timely decision-making, which in turn necessitates automated risk assessment. In this paper, we propose a mathematical model for quantifying data protection risks at run time. This model accounts for the specific properties of data protection risks, such as the time it takes to exploit a data protection vulnerability and the damage caused by such exploitation. Using this risk quantification, our approach can make, in an automated process, sound decisions on prioritizing data protection vulnerabilities dynamically. Experimental results show that our risk prioritization method leads to a reduction of up to 15.8% in the damage caused by data protection vulnerabilities.

Platform ecosystems have captured a variety of markets, enabling coordination, transactions, and value co-creation between independent actors. A focal platform constitutes the central nexus of e-commerce ecosystems and fosters the interaction among ecosystem participants through their boundary resources. Standardizing these interfaces simplifies ecosystem entry for developers and increases the number of participants propelling the network effects, and thus the overall value of the ecosystem. Currently, there is a lack of prescriptive design knowledge guiding platform owners in designing successful e-commerce ecosystems. Addressing this issue, we followed a dual approach, reporting on a systematic literature review in which we identified design requirements and complemented these with a multiple-case study on selected e-commerce ecosystems. Aggregating the requirements resulted in six meta-requirements and 19 design principles that foster the standardization of focal e-commerce platforms. Our design principles simplify the development of complements and enable multi-homing for developers due to possible standardization across ecosystems.

Platform ecosystems have captured a variety of markets, enabling coordination, transactions, and value co-creation between independent actors. A focal platform constitutes the central nexus of e-commerce ecosystems and fosters the interaction among ecosystem participants through their boundary resources. Standardizing these interfaces simplifies ecosystem entry for developers and increases the number of participants propelling the network effects, and thus the overall value of the ecosystem. Currently, there is a lack of prescriptive design knowledge guiding platform owners in designing successful e-commerce ecosystems. Addressing this issue, we followed a dual approach, reporting on a systematic literature review in which we identified design requirements and complemented these with a multiple-case study on selected e-commerce ecosystems. Aggregating the requirements resulted in six meta-requirements and 19 design principles that foster the standardization of focal e-commerce platforms. Our design principles simplify the development of complements and enable multi-homing for developers due to possible standardization across ecosystems.

Der Einsatz von IT-Systemen ist omnipräsent. Im Gegensatz zur Verbreitung der Systeme werden die Wirkungen der Systeme für Individuen, Unternehmen oder Gesellschaften selten betrachtet. Damit dürften viele Nutzer und Unternehmen von der Wirkung der Investition überrascht werden. Die Gefahr fehlerhafter Investitionen nimmt zu und mögliche Potenziale der IT bleiben ungenutzt.

Das Buch vermittelt wissenschaftlich fundiertes Wissen über die Wirkung und Wirtschaftlichkeit von IT-Systemen. Aufbauend auf Grundlagen aus der Organisationslehre, Soziologie, Entscheidungstheorie, Kosten- und Leistungsrechnung wird diskutiert, welche Phänomene durch IT-Systeme induziert werden. Die mannigfaltigen Wirkungen von IT-Systemen sowie Verfahren zur Wirkungsermittlung werden beschrieben. Sämtliche Aspekte für ein holistisches Wirkungsmanagement von IT-Systemen von der Projektskizze bis zur Umsetzung in der Realität werden in einem neuen Ansatz integriert.

Formulating design principles is the primary mechanism to codify design knowledge which elevates its meaning to a general level and applicability. Although we can observe a great variety of abstraction levels in available design principles, spanning from more situated to more generic levels, there is only limited knowledge about the corresponding (dis-)advantages of using a certain level of abstraction. That is problematic because it hinders researchers in making informed decisions regarding the (intended) level of abstraction and practitioners in being oriented whether the principles are already contextualized or still require effort to apply them within their situation. Against this backdrop, this paper (1) explores different abstraction levels based on a sample of 69 design principles from the chatbot domain as well as (2) provides a preliminary positioning framework and lessons learned. We aim to complement methodological guidance and strengthen the principles' applicability, leading to knowledge reuse.

Increasing digitization and the associated tremendous usage of technology have led to data of unprecedented quantity, variety, and speed, which is generated, processed, and required in almost all areas of industry and life. The value creation and capturing from data presents companies with numerous challenges, as they must create or adapt appropriate structures and processes. As a link between corporate strategy and business processes, business models are a suitable instrument for meeting these challenges. However, few research has been conducted focusing on data-based monetization in the context of data-driven business models so far. Based on a systematic literature review the paper identifies five key components and 23 characteristics of data-driven business models having crucial influence on data-based value creation and value capturing and thus on monetization. The components represent key factors for achieving commercial benefits from data and serve as guidance for exploring and designing suitable data-driven business models.

This expert voice paper presents a comprehensive rationale ofmulti-levelmodeling. It aims not only at a systematic assessment of its prospects, but also at encouraging applications of multi-level modeling in business information systems and at providing a motivation for future research. The assessment is developed from a comparison of multi-levelmodelingwith object-oriented, general-purpose modeling languages (GPMLs) and domain-specific modeling languages (DSMLs). To foster a differentiated evaluation, we propose a multi-perspective framework that accounts, among others, for essential design conflicts, different types of users, as well as economic aspects. Besides the assessment of the additional abstraction offered by multi-level modeling, the evaluation also identifies specific drawbacks and remaining challenges. Based on the results of the comparative assessment, in order to foster the adoption and further development of multi-level modeling, we discuss the prospects of supplementing multi-level modeling languages with multi-level programming languages and suggest possible dissemination strategies customized for different groups of users. The paper concludes with an outline of future research.

An important economic sector influenced by the development of platforms is e-commerce. The most successful companies in e-commerce employ platform business models and strive to provide other companies with application services. Despite growing economic importance and rising research interest, thus far, no attempts were made to structure existing research into platforms in e-commerce. Hence, a quantitative bibliometric analysis of 7,463 platform-related papers in the context of e-commerce was conducted. The papers were published in major conferences, journals, and books from 1993 to 2021. The authors identified a continuous development of platform research in e-commerce, with the continuous development characterized by three major periods of research. Furthermore, four clusters in platform research are outlined, i.e., business models, social commerce, infrastructure, and socio-technical characteristics. These clusters can serve as a foundation for future research. The conducted bibliometric analysis contributes to scientific research by offering an objective and systematic overview of platform research in e-commerce.

Die zurückliegenden Jahre haben deutlich gemacht, welche Bedeutung Innovationen im Biotechnologie- und Gesundheitssektor für Wirtschaft und Gesellschaft haben. Allgegenwärtig sichtbare Unternehmen wie Curevac und BioNTech zeigen, welchen zentralen Beitrag Ausgründungen aus den Lebenswissenschaften leisten können. Die Metropolregion Berlin hat als Ökosystem für Bio- und HealthTech Startups im vergangenen Jahrzehnt rapide an Bedeutung gewonnen. Während die Metropolregion Berlin bei digitalen Startups bereits führend ist, verbleiben für forschungsintensive Technologie-Startups im Bereich der Biotechnologie und Gesundheitswirtschaft Potenziale ungenutzt. Aus dem qualitativen und quantitativen Vergleich des Berliner Ökosystems mit dem europaweit führenden Ökosystem Cambridge (UK) sowie weiteren Standorten in Deutschland, haben wir sechs Kernherausforderungen herausgearbeitet. Diesen muss sich sich die Metropolregion Berlin stellen, um im Spitzenfeld der Ökosysteme für Bio \\\& HealthTech Startups weiter aufzuholen. Die wichtigste Herausforderung für Berlin stellt die Nachhaltigkeit eines vernetzten Ökosystems für forschungsintensive Bio- und HealthTech Startups dar. Zwar können gründungsinteressierte Wissenschaftlerinnen und Wissenschaftler prinzipiell auf erfolgskritische Ressourcen wie Talent, Wissen, Beziehungen, Patente und Kapital zurückgreifen, diese werden bisher jedoch nur unzureichend genutzt und sind häufig nicht in ausreichendem Maße vorhanden. Statt einem sich stetig verstärkenden regionalen Kreislauf, wie er sich im IT-Sektor entwickelt hat, geht im Bereich der

Digital data objects on viruses have played a pivotal role in the fight against COVID-19, leading to healthcare innovation such as new diagnostics, vaccines, and societal intervention strategies. To effectively achieve this, scientists access viral data from online communities (OCs). The social-interactionist view on generativity, however, has put little emphasis on data. We argue that generativity on data depends on the number of data instances, data timeliness, and completeness of data classes. We integrated and analyzed eight OCs containing SARS-CoV-2 nucleotide sequences to explore how community structures influence generativity, revealing considerable differences between OCs. By assessing provided data classes from user perspectives, we found that generativity was limited in two important ways: When required data classes were either insufficiently collected or not made available by OC providers. Our findings highlight that OC providers control generativity of data objects and provide guidance for scientists selecting OCs for their research.

Inthisresearchreport,wepresentanewversionofITModelingLanguage(ITML).Itis
integratedwiththefamilyofDomain-SpecificModelingLanguages(DSMLs)thatarepart
ofMulti-PerspectiveEnterpriseModeling(MEMO).Thedesignofthelanguagefolloweda
provenmethod.Itprovidesforanalysingrequirementsbasedontheanalysisofpossibleuse
scenarios.TheITMLwasspecifiedwiththemetamodelinglanguageMEMOMML.Duetothe
considerablesizeofthemetamodel,itspresentationissplitintoseveralpartialmetamodels,
whicharedescribedatalevelofdetailthatisrequiredfortheimplementationofthelanguage
withinamodelingtool.Thepresentationofthemetamodelissupplementedbydiscussionsof
designconflictsandrelateddecisions.Inadditiontotheabstractsyntaxandsemantics,which
arerepresentedbythemetamodel,wealsoproposeaconcretesyntax,whichwasdesigned
withthesupportofagraphicdesigner.Finally,wealsoprovideashortdiscussionofprincipal
limitationsofconventionalmetamodelingaswellasanoutlookonourfutureresearch.
Keywords:ITmanagement,enterprisemodeling,ITinfrastructure,ITML,MEMO,multi-level
modeling.

In recent years, the catchword “low‐code” has evolved into what can be seen as a major trend
in software development platforms. A growing number of vendors respond to this trend by
offering software development platforms that promise limited need for coding only and a tremendous
boost in productivity. Both aspects have been the subject of intensive research over
many years in areas such as domain‐specific modeling languages, model‐driven software development,
or generative programming. Therefore, the obvious question is how ʺlow codeʺ
platforms differ from such approaches and what specific performance features they offer.
Since there is no unified definition of “low‐code”, the only way to develop an elaborate understanding
of what it is – and might be – is to analyze the actual use of the term. For obvious
reasons, it is not promising in this respect to rely on marketing announcements made by vendors.
Instead, it seems more appropriate to examine “low‐code” platforms. This research report
presents a study of 10 relevant platforms, capturing and assessing common characteristics
as well as specific features of individual tools. The study is guided by a method that consists
of a conceptual framework, which provides a uniform structure to describe and compare “lowcode”
platforms, and a process model that describes the sequence of steps.

Understanding the role of Artificial Intelligence (AI) is crucial to contribute to sustainable development including the most fundamental challenges of our society, such as climate change, healthy lives, and inclusive economic growth. As Information Systems (IS) research has a great tradition of investigating how technology and methods can be employed to foster sustainability, this study follows widely accepted expectations that AI will boost this. Against this backdrop, the present study aims at revealing how and what purposes IS researchers use AI for sustainability. Based on a literature corpus of 95 articles, promising research in diverse fields has been found that underlines the great potential of IS in achieving economic, ecological, and social sustainability. In doing so, this study complements recent research streams on AI and sustainability from a IS perspective by providing a comprehensive overview of themes, topics, and clusters addressed within IS literature and discussing future avenues for research.

Studierende für einen Studiengang zu gewinnen, die die richtigen Erwartungen an und ausgeprägtes Interesse für das jeweilige Studienfach haben, stellt eine besondere Schwierigkeit dar, wenn das Fach nicht Teil des allgemeinbildenden schulischen Lehrplans ist. In Nordrhein‐Westfalen  (NRW) gilt dies nicht zuletzt  für das Studienfach Wirtschaftsinformatik. An der Universität Duisburg‐Essen wurde daher ein Schulbotschafter‐Programm für Wirtschaftsinformatik etabliert, welches auf die gezielte Information der studieninteressierten Oberstufenschülerinnen und ‐schüler in NRW gerichtet ist. Der vorliegende Forschungsbericht veröffentlicht die Vorgehensweise, Ergebnisse und Limitationen einer in diesem Kontext durchgeführten online‐Befragung von 313 Oberstufenschülerinnen und ‐schülern. Die Ergebnisse zeigen ein differenziertes Bild präferierter Informationsangebote und ‐veranstaltungen. Die ausgewerteten Antworten zum Studienfach Wirtschaftsinformatik machen darüber hinaus deutlich, dass fehlende bzw. fehlerhafte Vorstellungen über das Fach weit verbreitet sind und – für eine effektive Unterstützung bei der Studienwahl – die Ansprüche und Möglichkeiten eines Wirtschaftsinformatikstudiums gezielt zu vermitteln sind.

Das Fach Wirtschaftsinformatik hat schon seit Jahrzehnten einen festen Platz an den Universitäten in Deutschland. Die Nachfrage nach Absolventen des Fachs ist ungebrochen hoch. Gleichzeitig steht die Disziplin vor der Herausforderung, sich gegenüber anderen anwendungsorientierten Informatikstudiengängen und nicht zuletzt gegenüber den an Fachhochschulen immer stärker werdenden praxisnahen Studienangeboten abzugrenzen.

Es gibt bislang kaum Veröffentlichungen, die das Studienfach Wirtschaftsinformatik an Hochschulen in Deutschland empirisch untersuchen. Der vorliegende Forschungsbericht soll diese Lücke füllen, indem er die aktuelle Situation der universitären Wirtschaftsinformatik als Anbieter von grundständigen und weiterführenden Studiengängen in Deutschland beleuchtet. Er nutzt dazu Studierendenzahlen des jüngsten CHE-Rankings und des statistischen Bundesamtes (2016, 2018, 2019). Die Analyse wertet die Studierendenzahlen und Frauenanteile differenziert nach Bachelor- und Masterstudiengängen aus und berücksichtigt dabei auch deren Zugehörigkeit zu bestimmten Fakultäten, zu Bundesländern bzw. Regionen sowie zu bestimmten Hochschultypen.

Im Ergebnis wird ein facettenreiches Bild der in vielerlei Hinsicht heterogenen universitären Wirtschaftsinformatik in Deutschland gezeichnet. Vor dem Hintergrund der gewonnenen Einblicke in die Wettbewerbssituation zur benachbarten Informatik sowie zu alternativen Hochschultypen werden abschließend Forschungsfragen für zukünftige Arbeiten formuliert.

Despite occasional pleas to incorporate the ethics of information systems into the field’s research agenda, the analysis of the moral ramifications of information systems has remained unsystematic in nature. Work on a remarkable variety of ethical issues has appeared, but the field has yet to produce a coherent conception of how it construes and studies the ethics of information systems. In this research-in-progress paper, we report on work to redress the situation by addressing three goals. First, we provide an overview of contributions made to the study of ethics in information systems research in recent decades. Second, we present a classificatory scheme to organize past and future work on the subject. Third, we identify themes that have received little attention to date, proposing routes for future work. In particular, we find that our field has yet to fully explore the moral implications of the very artifacts of its own design. We conclude with a call to action for information systems researchers to work towards a structured account of ethics as part of the field’s research agenda.

The spread of the Internet of Things offers companies the potential to exert a disruptive influence on existing market structures and entire domains. The shift from product to service orientation and the integration of the customer as a value co-creator makes the identification and development of value-adding, IoT-based offerings a central challenge. As a link between strategy and business processes, business models are a suitable tool to meet this challenge. However, present business models lack of consideration of IoT specific characteristics. Against this background we provide a taxonomy for the description of IoT-based business models based on systematic literature research. Furthermore, the taxonomy is applied to 103 business models, demonstrating its usefulness. We also provide insights into the design of business models within two domains. The taxonomy provides a tool for investigating busi-ness models, especially how IoT can be incorporated into them and also a conceptual basis for future research.

Nanotechnology is no longer science fiction. For more than half a century, the manipulation of matter at the atomic level has been an integral part of the methodological framework of a wide range of disciplines, e.g., physics, chemistry, biology. The fusion of nanotechnological approaches with the paradigm of the Internet of Things led to the creation of a new type of smart, internet-connected objects on the nanoscale at the beginning of the last decade under the term Internet of Nano Things. Despite the growing interest in research and practice, however, there is a lack of a basic, methodologically sound classification of methodological approaches and concepts that not only names them, but also shows their characteristics and forms of expression in order to create a common understanding within the domain. To address this shortcoming, the paper presents a taxonomy for IoNT-based systems to provide a conceptual basis for future research.

Im Rahmen der Digitalisierung nehmen smarte Produkte und die darauf aufbauenden intelligenten Dienstleistungen einen immer größeren Platz sowohl im betrieblichen Kontext als auch im Endkundenbereich ein. Auslöser hierfür stellt vor allem die leistungsfähigere und kostengünstigere Hardware dar, welche es Unternehmen ermöglicht, zunehmend Produkte mit intelligenten und vernetzten Komponenten auszustatten. Diese smarten Produkte bieten Unternehmen und Kunden völlig neue Möglichkeiten zur Interaktion, bieten neue Mehrwerte und beeinflussen die unternehmerische Wertschöpfung an sich. Ziel dieses Beitrages ist es, einen Einstieg in das Themenfeld der smarten Produkte und Dienstleistungen zu geben und aufzuzeigen, welche Möglichkeiten diese für den Endnutzer und für Unternehmen eröffnen.

Unveränderter Original-Beitrag Strobel et al. (2019) Von smarten Produkten zu smarten Dienstleistungen und deren Auswirkung auf die Wertschöpfung, HMD – Praxis der Wirtschaftsinformatik 56, 494–513.  https://doi.org/10.1365/s40702-019-00520-x

The business value of IT in companies is a highly discussed topic in information systems research. While the IT business value is an agreed upon term, its decomposition and assessment on a more detailed level is ambiguous in literature and practice. However, assessing the IT business value is pivotal for goal-oriented IT management. Therefore, we suggest a hierarchical decomposition of the IT business value along aggregated impacts and atomic impacts. We introduce a taxonomy to gain a better understanding of what types of atomic impacts may be caused by IT investments. With the help of the taxonomy, we classify a total of 957 values from existing value catalogs and derive 29 archetypal IT impacts grouped by a company’s business units. Bundling this grouping with exemplary impacts for the IT value assessment, we finally propose an IT value meta-framework for the structured business value assessment.

Multi-sided markets (MSMs) have entered the retail sector as digital marketplaces and have proven to be a successful business model compared to traditional retailing. Established retailers are increasingly establishing MSMs and also participate in MSMs of pure online companies. Retailers transforming to digital marketplaces orchestrate formerly independent markets and enable retail transactions between participants while simultaneously selling articles from an own assortment to customers on the MSM. The retailer’s dual role must be supported by the retail information systems. However, this support is not explicitly  represented in existing reference architectures (RAs) for retail information systems. Thus, we propose to develop a RA for retail information systems facilitating the orchestration of supply- and demand-side participants, selling own articles, and providing innovation platform services. We apply a design science research approach and present seven architectural requirements that a RA for MSM business models needs to fulfill (dual role, additional participants, affiliation, matchmaking, variety of services, innovation services, and aggregated assortment) from the rigor cycle. From a first design iteration we propose three exemplary, conceptual architectural patterns as a solution for three of these requirements (matchmaking for participants, innovation platform services, and aggregated assortment).

Graduates of Business Informatics (BI) have excellent job perspectives. The ongoing digital transformation entails the fascinating opportunity for our students to participate in designing future organizations. At the same time, the analysis of statistical data indicates that first-year-student numbers at Germany’s University bachelor programs in BI are relatively low. Personal experience additionally suggests that many first-year-students have no clear idea about BI and their future role in practice. Hence, we assume that already the perception of BI by students at secondary schools is biased by substantial misconceptions. This paper is intended to contribute to the debate on how to raise the awareness of upper secondary school students for BI. Based on an exploratory survey and practical experience through a case study teaching program employed by "school ambassadors", we propose critical success factors for designing initiatives to disseminate a realistic and attractive image of BI and the professional perspectives it enables.

Based on the cultural, social and technological development of the last hundred years, the pursuit of health driven by primal instincts has been transformed in most areas worldwide into a quasi de facto standard. But this security is deceptive. Not only the global developments of the last few months, but also creeping factors such as demographic change or the steadily growing world population are putting increasing pressure on the healthcare system. Today, more and more health care systems based on continuous demand for medical resources are increasingly reaching their limits. Technologies such as the Internet of Things are not a panacea, but offer great potential for increasing the flexibility and efficiency of healthcare systems. However, the development of such IoT-based healthcare systems requires a holistic understanding of the information technology as well as the domain itself. Against this background, the paper presents a domain-specific modelling language for IoT-based healthcare systems

Richard Feynman’s visionary lecture at Caltech, which dates back more than half a century, is regarded as the birth of today's nanotechnology. Over time, many nanotechnology-based approaches, methods, and innovations have been adopted in almost all research disciplines. This nano-centered evolution is currently transforming the traditional paradigm of the Internet of Things into the Internet of Nano Things. However, the focus here is not on the mere adaptation of down scaling and is instead primarily on the effects and characteristics that result from this new scale. To fully exploit these new possibilities and combine them with existing added-value technologies, it is not sufficient to miniaturize existing Internet-of-Things- based systems—they must be developed from scratch. Against this background, this study examines the main areas of nanotechnology in combination with the Internet of Things phenomenon and, based on an exploratory literature search, presents an information system architecture for IoNT-based information systems.

Based on the technological developments of the last few years and the associated digitalisation, the Internet of Things is now an essential part of practically every aspect of life. Smart products with their sensors and actuators are not only boundary objects between the physical and digital world, but also tie both worlds more and more together. The capabilities of the products range from simple monitoring tasks by drones in agriculture to autonomous use in mining. However, in order to exploit the full potential of these capabilities, it is not enough to use individual smart products or sensors, it is necessary to develop holistic IoT-based information systems from the ground up. To take such a systemic perspective, it is essential to have a sound conceptual understanding of the domain and a common language. Against this background, the publication presents a domain-specific modelling language for IoT-based information systems.

Deep Tech is receiving increasing attention from investors and policy as a means to solve the most pressing societal challenges, leverage new business opportunities, and increase global economic growth. To respond to the increasing need to fundamentally understand deep tech and its implications for business and innovation policy, this PDW sets out to establish a shared understanding among information systems researchers of how we can build strong research within IS and with other management sub-disciplines. The PDW will start with a dynamic panel discussion among IS scholars with interests in deep tech from different perspectives in the disciplines (i.e. three broad themes), followed by semi-structured roundtable discussions with participants to shape emerging research opportunities for future deep tech research. The results of the workshop will be integrated into a joint statement that spells out the conceptual background of the topic and sheds light on future research directions.

With the advent of end-user and cloud computing, business users can implement information systems for work practices on their own – either from scratch or as extensions to existing systems. The resulting information systems, however, often remain hidden from managers and official IT units, and are therefore called “shadow IT systems”. When a shadow IT system is identified, the organization has to decide on the future of this system. The study uses a configurational perspective to explain outcomes of shadow IT system identification, as well as the mechanisms and contextual conditions which bring them about. For this purpose, 27 profiles of shadow IT systems were compiled by conducting 35 interviews with respondents from different positions and industries. The analysis gives insight into six distinct context-mechanism-outcome configurations explaining four outcomes that occur after shadow IT system identification, namely phase-out, replacement, continuing as IT-managed system, and continuing as business-managed system. These results contribute to the shadow IT literature and, more broadly, IS architecture and governance streams of the IS literature. They inform IT managers when these weigh decision options for identified shadow IT systems given different contextual conditions.

Multi-sided markets (MSMs) have entered the retail sector as digital marketplaces and have proven to be a successful business model compared to traditional retailing. Established retailers are increasingly establishing MSMs and also participate in MSMs of pure online companies. Retailers transforming to digital marketplaces orchestrate formerly independent markets and enable retail transactions between participants while simultaneously selling articles from an own assortment to customers on the MSM. The retailer's dual role must be supported by the retail information systems. However, this support is not explicitly represented in existing reference architectures (RAs) for retail information systems. Thus, we propose to develop a RA for retail information systems facilitating the orchestration of supply-and demand-side participants, selling own articles, and providing innovation platform services. We apply a design science research approach and present seven architectural requirements that a RA for MSM business models needs to fulfill (dual role, additional participants , affiliation, matchmaking, variety of services, innovation services, and aggregated assortment) from the rigor cycle. From a first design iteration we propose three exemplary, conceptual architectural patterns as a solution for three of these requirements (matchmaking for participants, innovation platform services, and aggregated assortment).

Music is a central instrument in video gaming to attune a player’s attention to the current atmosphere and increase their immersion in the game. We transfer the idea of scene-adaptive music to car drives and propose SoundsRide, an in-car audio augmented reality system that mixes music in real-time synchronized with sound affordances along the ride. After exploring the design space of affordance-synchronized music, we design SoundsRide to temporally and spatially align high-contrast events on the route, e.g., highway entrances or tunnel exits, with high-contrast events in music, e.g., song transitions or beat drops, for any recorded and annotated GPS trajectory by a three-step procedure. In real-time, SoundsRide 1) estimates temporal distances to events on the route, 2) fuses these novel estimates with previous estimates in a cost-aware music-mixing plan, and 3) if necessary, re-computes an updated mix to be propagated to the audio output. To minimize user-noticeable updates to the mix, SoundsRide fuses new distance information with a filtering procedure that chooses the best updating strategy given the last music-mixing plan, the novel distance estimations, and the system parameterization. We technically evaluate SoundsRide and conduct a user evaluation with 8 participants to gain insights into how users perceive SoundsRide in terms of mixing, affordances, and synchronicity. We find that SoundsRide can create captivating music experiences and positively as well as negatively influence subjectively perceived driving safety, depending on the mix and user.

Am ICB gibt es mit fünf vollen Professuren eine der deutschlandweit größten Wirtschaftsinformatik-Fachgruppen. Für einen solch großen Forschungsstandort ist die Anzahl der Erstsemesterstudierenden im Bachelorstudiengang Wirtschaftsinformatik (WI) seit einiger Zeit auf einem bedenklich niedrigen Niveau. Dies gilt nicht zuletzt im Vergleich zum konkurrierenden Studiengang Angewandte Informatik – Systems Engineering, der ebenfalls am ICB angeboten wird.

Umfragen unter Studieninteressierten aus NRW deuten darauf hin, dass sie mehrheitlich keine klare Vorstellung oder gar Fehlvorstellungen bzgl. des Studienfachs Wirtschaftsinformatik besitzen (Schauer und Schauer 2021). Um Ansatzpunkte zur besseren Profilierung des WI-Bachelorstudiengangs zu identifizieren, wurden zwei Befragungen unserer WI-Erstsemesterstudierenden durchgeführt (Ende 2018 und 2019). Der vorliegende Forschungsbericht wertet die Antworten der Studierenden aus. Er liefert differenzierte Einblicke u.a. bzgl. ihrer Beweggründe für die Wahl von Essen als Studienort, die Studienfachwahl sowie ihrer Einstellung zum Fach Wirtschaftsinformatik und den wahrgenommenen Herausforderungen eines universitären Studiums. Er fasst wesentliche Ergebnisse der Befragung in Form von Thesen zusammen und leitet Vorschläge für Maßnahmen ab, die geeignet erscheinen, die Wahrnehmung des Studienfachs Wirtschaftsinformatik zu verbessern.

Bei Interesse an dem vollständigen Forschungsbericht wenden Sie sich gerne an die Autorin Carola Schauer

Der vorliegende Beitrag zeigt am Beispiel der betriebswirtschaftlichen Organisationslehre und der Wirtschaftsinformatik auf, dass die Beschränkung auf tradierte disziplinspezifische Perspektiven nicht geeignet ist,den vielschichtigen Auswirkungen der digitalen Transformation gerecht zu werden. Vor diesem Hintergrund werden die Potentiale einer engen, trans-disziplinären Zusammenarbeit dargestellt. Dazu werden zunächst die für einesolche Zusammenarbeit erforderlichen Gemeinsamkeiten herausgearbeitet. Dabei wird insbesondere die Rolle der Sprache gewürdigt. Sie ist sie sowohl zur Untersuchung von Handlungssystemen als auch zur Gestaltung und Nutzung von Informationssystemen von zentraler Bedeutung, entfaltet dabei aber durchaus ambivalente Wirkungen. Darauf aufbauend werden grundlegende Zielkonflikte, etwa zwischen Standardisierung und Fortschritt oder zwischen loser und enger Kopplung betrachtet und Ansätze zur ihrer Entschärfung aufgezeigt. Daneben geht der Beitrag auf die Auswirkungen ein, die induktive Verfahren der „Künstlichen Intelligenz“ auf das Handeln in Unternehmen einerseits, auf die wissenschaftliche Forschung andererseits erwarten lassen –und welche wissenschafts-theoretischen Herausforderungen damit verbunden sind. Auch wenn vorwiegend auf spezifische Forschungsfragen der Organisationslehre und der Wirtschaftsinformatik fokussiert wird, sollte die Untersuchung auch für andere Teildisziplinen der Betriebswirtschaftslehre bedeutsam sein.

A sustainable and climate-friendly energy supply needs flexible and efficient distribution systems. Key factors to implement this kind of systems are intelligent coordination (smart grid approaches) and the integration of different energy sectors. This article introduces the unified energy agent as an agent-based approach for a comprehensive modelling and control of energy conversion systems. This approach enables both the simulation and optimization of coupled energy networks, and then in a next step, the development of corresponding smart grid solutions to be applied in the field. Its applicability for the simulation of coupled networks is presented by a real-world use-case of an innovative combined heat and electrical network, which was implemented for the city of Lemgo, Germany. Preliminary results from the project are discussed and an outlook on future work is given.

Colors surround us in all life situations and have the power to influence our mood and emotions, which makes color a crucial impact factor for decision making in ecommerce environments. Therefore, this research paper aims to explore the psychological and physiological effects of color use on websites with a neuroimaging method. For this, an experiment was designed in which 24 healthy participants watched an online shoe shop in 4 different colored versions during which their neural activity in the prefrontal cortex was measured. While comparing the neural activity between the different employed colors, distinct implications can be derived. That is, in comparison to the blueish website, (1) grey scaled websites require higher cognitive load but are rated as aesthetically pleasing, (2) greenish websites result in more negative valence while they require not more neural resources, and (3) reddish websites are rated low in valence and require higher neural processing resources.

Social robots increasingly diffuse into our lives in work, health, and many other areas. However, theoretical approaches that explain how social robots should be designed to maximize experiential and performance-related outcomes in human-robot interaction (HRI) are still rare. To close this research gap, we aim to develop a dual process model of HRI with the help of two experiments. Results of the first experiment show that individuals categorize humans and robots differently in the automatic and reflective system, leading to different forms of robotic biases in these systems. Specifically, whereas humans show a bias against all types of robots in the reflective system, they only show biases against robots with low anthropomorphism in the automatic system. With the second experiment, we aim to complement these results from a neurophysiological perspective to gain more insights into cognitive processes during classification and evaluation of robots.

This chapter presents a method for multi-perspective enterprise modeling (MEMO). Enterprise modeling fundamentally aims to support the conjoint analysis of business and IT to foster their integration. MEMO expands on this general aim with a specific concern for the professional perspectives of different stakeholder groups. MEMO is based on a language architecture that comprises an extensible set of domain-specific modeling languages, each addressing one or more professional perspectives. It is supplemented by an adaptable generic framework to support high-level ‘ballpark' views of an enterprise and to serve as a common starting point for more elaborate analysis and design tasks. MEMO also supports the construction of corresponding process models to design customized modeling methods. The chapter motivates the use of MEMO and illustrates possible use cases. It also provides a description of the method's architecture, its DSMLs, and a tool environment that supports the development and analysis of enterprise models.

For most car and truck manufacturers access to information about the status of produced vehicles end with their sale. With embedded connectivity units this changes so that manufacturers can gather data from vehicle in-build sensors and thus, gain insights into each products usage. Our study investigates why manufacturers aim to integrate connectivity units into their products to gather sensor based usage information and what hinders them to do so. Thereby, we aim to identify the factors that have an influence on the decision of vehicle manufacturers to adopt the concept of the vehicle digital twin. To unveil those factors, we conducted 30 expert interviews at two vehicle manufacturers in which we found benefits and barriers regarding the realization of a product digital twin. By conceptualizing the benefits and barriers, which have a positive or negative influence on the adoption decision from the perspective of the manufacturers, we were able to derive general influences on the adoption decision. In our adapted technology-organization-environment framework we found influences in the technological (i.e. product data and product heterogeneity), the organizational (i.e. business model orientation, readiness of internal processes and digital culture) and the environmental (i.e. competitors behaviour, legal regulations and customer demand) dimension.

Health and well-being have been among the essential needs of humanity since the beginning of time. The healthcare systems are coming under more and more pressure due to a constantly growing world population, demographic change and steady rising of chronic disease rates. Through these circumstances, traditional healthcare systems may soon reach their limits and medical resources are becoming an increasingly valuable commodity. Modern technologies like the Internet of Things offer based on their application possibilities great potential for increasing among others flexibility, efficiency and cost-effectiveness of the healthcare system. To ensure such an IoT based healthcare for patients, holistic information and communication technology solutions are required that integrate both system-relevant technological and human aspects. Against this background, we present a generic information system architecture for smart health systems, based on a systematic literature driven explorative analysis of the domain.

Services are becoming increasingly important, and service systems are seeing the use of service-dominant logic to understand value creation through the integration of active and passive resources. Digital transformation is significantly influencing service systems, and new, smart technologies are enabling innovative value propositions, leading to smart service systems. Smart products, which are a part of the Internet of Things, are the main building blocks of such systems. Attempts have been made to conceptualize smart service systems, but there seems to be no consensus in the literature because, for example, smart products have not been defined in a consistent way. We therefore examine ways to classify smart service systems in terms of their characteristics and attributes. We develop a taxonomy based on a systematic literature review focusing on smart features. Furthermore, an evaluation using domain-specific use cases demonstrates the applicability of the taxonomy. Our contribution combines and extends the available conceptualizations regarding smart service systems to pave the way for the necessary future research.

Food has been a fundamental human need since the beginning of time. Agriculture, as the central foundation of global food production, is increasingly coming under pressure from the growing world population. Even today, it´s no longer possible to guarantee sufficient food security in the long term and 10% of humanity goes to bed hungry every night. Given the expected increase in the world’s population based on today’s figures and an associated more than 70% necessary increase in food sector production, the question arises whether this is feasible using classical methods and approaches. The use of modern information and communication technology alone is certainly not a panacea. Despite all this, technologies, such as the Internet of Things, show great potential for the development of more productive and cost-effective but, above all, more sustainable agriculture. However, developing such a solution requires more than a purely technical point of view. Only by creating a holistic information technology solution that takes not only a technological but also a plant, animal, human and therefore holistic perspective can real progress be made. Against this background, this paper represents the publication of a generic information system architecture based on a systematic literature-driven explorative analysis of the domain.

Blue of all colors seems to be generally preferred by humans and animals. Consequently, the use of this color in ecommerce context has several positive effects such as increased trustworthiness and aesthetic ratings. These effects are, in this study, hypothesized to be caused by specific neural processes in the prefrontal cortex of human decision makers. Consequently, this study tackles the research question whether there is a distinct neural activation pattern for blue websites that helps to explain why blue is often most favored. To investigate this, one website is designed and manipulated in col-or to which user reactions are measured by employing functional near-infrared spectroscopy (fNIRS). The results of this study show that blue colored websites seem to require generally less processing power related to cognitive while revealing increases in brain structures related to processing pleasant and aesthetic stimuli.
 

Whether males and females evaluate ecommerce websites differently has long been discussed and has resulted in inconsistent research findings. While some studies identified gender differences in the evaluation of websites, other studies indicate that these differences are inexistent. To shed light on these hypothetical gender differences on ecommerce website perceptions, a behavioral and functional near-infrared spectroscopy (fNIRS) experiment in which participants had to use and evaluate three different ecommerce websites was conducted. While the questionnaire-based behavioral results showed no significant differences between gender, neural gender differences could be discovered. In particular, well rated websites resulted in increased neural activity for men in brain regions of the dlPFC and vlPFC in the left hemisphere, while the lower evaluated websites resulted in an increased neural activity in brain regions of the vmPFC for men in the right hemisphere. Consequently, the results suggest that men seem to require higher neural activity for the emotional appraisal of, and decision making on ecommerce websites.

The ever increasing intra- and inter-competition, increased costs and a lower differentiation margin have led to intense competitive pressures within the domains of wholesaling and retailing. At the same time the increasing digitization due to technological innovation will radical change the economical and procedural fundamentals. In addition, from an entrepreneurial point of view, it must also be considered that the complexity of decision-relevant framework conditions has increased. Digitalisation is therefore to be seen as an essential driver for optimising business processes and as the basis for a new understanding of products and services. However, it cannot be considered independently of other social trends. The chapter will elaborate the underlying drivers and technological trends empowering the transformation processes within the domain of wholesaling and reailing. Starting from these major drivers we will scrutinize the impact of technological advancements and the opportunities, risks and constraints which are connected with it.

The Internet of Things and associated smart products are finding application in evermore domains. Within agriculture it is described under the term smart farming. Using smart products allows farmers to automatically record relevant information, monitor operating procedures or remotely control machines. To make these capabilities usable for added value, not only smart products but entire information systems that align to the domain and its requirements are necessary. Within the literature, various architectures can be found already. However, many lack a methodical foundation or an abstraction of application cases and technology. Against this background, the article presents an information system architecture independent of application cases or technology and oriented toward the domain of smart farming. Starting point of the development is a systematic literature review, based on Webster and Watson in combination with Vom Brocke, based on 18 existing architecture approaches that are analyzed and aggregated.

Organizations are increasingly challenged to digitally transform themselves, and to respond to calls for increased sustainability. While the adoption of sustainable innovations, such as Green information systems (Green IS), are one way to address both challenges, there are only few insights that provide non-technology or company-specific insights into specific positive and negative Green IS outcomes. We address this shortcoming and shed light on Green IS adoption outcomes, as well as their interconnection to general sustainability initiatives in organizations. In a descriptive survey we find that many organizations already employ sustainability principles, but few incorporate Green IS. We confirm organizations almost exclusively report positive outcomes of Green IS usage, such as reduced resource consumption, increased compliance with regulations, and social acceptance. Based on these findings we suggest to especially further research the process of Green IS adoption.

Self-tracking solutions have become globally widespread, as they promise numerous advantages (e.g. improving health) to their users. Despite their benefits, such solutions are often abandoned due to quality issues. This phenomenon can also be observed for digitized products in general. As self-tracking solutions are hybrid products, combining digital and physical components, traditional domain-independent and abstract quality models like the prominent ISO 25000 standard seem to not cover quality in an appropriate way. We address these issues by answering the research question of which factors affect quality perceptions of different stakeholder groups when interacting in a wearable ecosystem. We use a systematic literature review based on a research protocol to identify and analyze 98 quality-influencing factors from 19 studies that we cluster in a map. The identified factors are compared to the ISO 25000 standard, showing that certain factors like hedonic motivation are unconsidered thoroughly in the existing standard.

In recent years, new types of interactive analytical dashboard features have emerged for operational decision support systems (DSS). Analytical components of such features solve optimization problems hidden from the human eye, whereas interactive components involve the individual in the optimization process via graphical user interfaces (GUIs). Despite their expected value for organizations, little is known about the effectiveness of interactive analytical dashboards in operational DSS or their influences on human cognitive abilities. This paper contributes to the closing of this gap by exploring and empirically testing the effects of interactive analytical dashboard features on situation awareness (SA) and task performance in operational DSS. Using the theoretical lens of SA, we develop hypotheses about the effects of a what-if analysis as an interactive analytical dashboard feature on operational decision-makers' SA and task performance. The resulting research model is studied with a laboratory experiment, including eye-tracking data of 83 participants. Our findings show that although a what-if analysis leads to higher task performance, it may also reduce SA, nourishing a potential out-of-the-loop problem. Thus, designers and users of interactive analytical dashboards have to carefully mitigate these effects in the implementation and application of operational DSS. In this article, we translate our findings into implications for designing dashboards within operational DSS to help practitioners in their efforts to address the danger of the out-of-the-loop syndrome.

Die Bedeutung von sog. Cloud-Services hat in den vergangenen Jahren deutlich zugenommen. Hiermit einher gehen unterschiedlichste Zweifelsfragen und Auseinandersetzungen mit der Finanzverwaltung im Rahmen von Betriebsprüfungen. Dies ist der Tatsache geschuldet, dass regelmäßig große Unsicherheit auf drei Ebenen besteht: Es ist erstens für die Steuerabteilung oder den Berater nur schwer nachvollziehbar, welche konkreten Leistungen sich hinter einem Begriff wie “Cloud-Aufwendungen” verbergen und wie diese Leistungen technisch erbracht werden. Auf einer zweiten Ebene herrscht regelmäßig Unsicherheit im Hinblick auf die zivilrechtliche Kategorisierung entsprechender Verträge und Leistungsbeziehungen. Schließlich ist auf einer dritten Ebene regelmäßig unklar, wie sich die steuerliche Behandlung darstellt. Das kann unter anderem Themen wie Quellensteuereinbehalt/beschränkte Steuerpflicht, die Hinzurechnungsbesteuerung oder auch die gewerbesteuerliche Hinzurechnung betreffen. Der vorliegende Beitrag widmet sich letzterer und hierbei insbesondere der sog. Infrastructure as a Service (IaaS) als einer wesentlichen Art von Cloud-Diensten.

Enterprise Architectures (EAs) are commonly visualized in the form of text, numbers, tables, graphs, models, and diagrams. These information visualization types are used to describe EAs in today’s organizations, but often lack an intuitive representation. In this paper, we provide another form of EA visualization utilizing the city metaphor. This spatial metaphor is suitable for visualizing complex information structures and potentially facilitates easy understanding of EAs, especially for non-IT staff. Based on a literature review and three rounds of open card sorting, we mapped eleven classes of EA objects to city elements. Our results enabled us to develop a formal language that allows an implementable and human-readable specification of various views, which we call EA City. We created an early stage 3D EA City prototype to demonstrate its applicability. Our model provides a solid foundation for further work on the city metaphor in the context of EA visualization.

In recent years, the “Internet of Things” with so called “smart products” has obtained increasingpopularity in both practice and research. By building on the capabilities of smart products, servicestransform to “smart services” emphasizing the value smart products can provide and how it is co- created. Even though first attempts have been conducted to conceptualize and classify smart services, there seems to be no overall consensus on the specific characteristics of smart services, which different forms they can take on and how different smart services can be described. For example, existing research on smart services does not always consider the common service design elements “servicecontent” and “service delivery”. To address this shortcoming, we develop a taxonomy of smart services by applying extant literature. We further demonstrate the usefulness of our taxonomy by classifying 50 empirical objects and presenting three cases. As a contribution, the paper enhances the understanding of the notion of smart services and strengthens the conceptual foundation for future smart service research.

The digital transformation creates an increasing demand for
projects to prepare and realize change. The professional management of
projects demands for methods. In particular, there is not alone need for
method engineering, but also for managing the use of methods and for
method maintenance. In this paper, it will be shown that traditional
approaches to method engineering are not only limited with respect to
reuse, they also do not support the integration of method engineering and
method management. The approach presented in this paper addresses
these limitations. It is based on a mult-level language architecture, which
enables the common representation of models and code.

Mit der digitalisierungsbedingten Zunahme kontinuierlich erfasster Massendaten aus unterschiedlichsten Quellen entsteht die Hoffnung, einen besseren Zugang als je zuvor zur Realität zu erhalten. Angesichts des Big-Data-Phänomens stellt sich dabei für Handelsunternehmen die Frage, welche unternehmensweite Datenstrategie es zu verfolgen gilt. Dazu liefert der folgende Beitrag anhand eines Frameworks eine sachlogische Struktur für eine unternehmensweite Datenstrategie. Für jedes aufgezeigte Strategiefeld dieses Frameworks sind dabei Basisentscheidungen zu treffen, die die nötigen Voraussetzungen zur Nutzung von Daten für erfolgreiche Einzelprojekte als auch die erfolgreiche Eingliederung datengetriebener Aktivitäten in Standardprozesse schaffen. Neben der Datenstrategie wird auch der realisierbare betriebswirtschaftliche Beitrag für Einzelhändler anhand einer Fallstudie entfaltet. Dazu wird auf das Handelsmarketing und den Marketing-Mix als zentrales Konzept, und seit jeher eines der wichtigsten Tätigkeitsfelder im Einzelhandel, zur Aufstellung einer datengetriebenen Entscheidungsphänomenologie zurückgegriffen. Als Antwort auf die Frage, welche Datenstrategie angesichts von Big Data von einem Einzelhändler zu verfolgen ist, wurden verschiedene Teilbereiche identifiziert und Maßnahmen innerhalb dieser ausgearbeitet. Es wurde gezeigt, dass integrierte und kohärente Maßnahmen auf organisationaler und technologischer Ebene für die Sammlung, Speicherung, Verarbeitung, Verwendung, Steuerung und Transformation von Big Data im Unternehmen nötig sind. Mit Erfüllung der notwendigen Vorrausetzungen für Big Data im Rahmen der Datenstrategie ist es dabei möglich nicht nur die hier aufgezeigte Absatzseite der Unternehmung zu optimieren, sondern auch die tiefgreifende Integration der verschiedenen Prozessbereiche im Handelsunternehmen abzubilden.

Durch die Digitalisierung befinden sich Unternehmen oftmals in der Umstellung zu digitalen Geschäftsprozessen und Geschäftsmodellen. Dies bietet viele neue Chancen für Innovationen durch den Einsatz neuer Konzepte und Technologien. Um diese Chancen nutzbar zu machen, können Servicesysteme eingesetzt werden. Der Beitrag gibt einen Überblick über dieses Konzept und zeigt auf, wie Servicesysteme charakterisiert und entworfen werden können. Ein Servicesystem stellt ein soziotechnisches System dar, das auf die Unterstützung der gemeinsamen Wertschöpfung abzielt, indem verschiedene interne und externe Ressourcen integriert und kombiniert werden. Der Entwurf erfolgt im Rahmen des Service Systems Engineerings in meist agilen Prozessen mit dem Ziel einer frühen Markterprobung. Dabei kann der Innovationsgedanke explizit berücksichtigt werden. Vorhandene Entwurfsansätze sind jedoch meist abstrakt und daher weniger für den konkreten Entwurf geeignet. Es können daher wesentliche Faktoren identifiziert werden, die die Entwicklung von Servicesystemen beeinflussen. Der Beitrag schafft einen Überblick über den aktuellen Stand der Forschung und zeigt Ansatzpunkte für eine Verbesserung der Nutzbarmachung des Konzeptes Servicesystem.

Im Rahmen der Digitalisierung nehmen smarte Produkte und die darauf aufbauenden intelligenten Dienstleistungen einen immer größeren Platz sowohl im betrieblichen Kontext als auch im Endkundenbereich ein. Auslöser hierfür stellt vor allem die leistungsfähigere und kostengünstigere Hardware dar, welche es Unternehmen ermöglicht, zunehmend Produkte mit intelligenten und vernetzten Komponenten auszustatten. Diese smarten Produkte bieten Unternehmen und Kunden völlig neue Möglichkeiten zur Interaktion, bieten neue Mehrwerte und beeinflussen die unternehmerische Wertschöpfung an sich. Ziel dieses Beitrages ist es, einen Einstieg in das Themenfeld der smarten Produkte und Dienstleistungen zu geben und aufzuzeigen, welche Möglichkeiten diese für den Endnutzer und für Unternehmen eröffnen.

In den letzten Jahren wurde die Digitalisierung verstärkt vor dem Hintergrund desInternets der Dinge betrachtet, bei dem jegliche Bestandteile des täglichen Lebens zu intelligenten Objekten (Smart Products) werden und mit dem Internet verbunden sind. Aufbauend auf den Smart Products entstehen neue digitale Dienstleistungen, sogenannte Smart Services. Mit diesen intelligenten Dienstleis- tungen werden völlig neue Wertschöpfungspotenziale erschlossen, die sich eben- falls auf die Geschäftsmodelle von Unternehmen auswirken. Ziel dieses Beitrages ist es, einerseits einen allgemeinen Einstieg in den Themenkomplex der Smart Services zu bieten und selbige andererseits spezifisch vor dem Hintergrund ihres Wertschöpfungspotenzials für Geschäftsmodelle und Ökosysteme näher zu beleuchten.

Information systems are at the core of the digital transformation. To cope with the dynamics of new, emerging markets and ever changing requirements, it is often argued that agile approaches to software development are mandatory. Some even demand to develop information systems without conceptual models, because they were likely to be outdated even before the software is implemented. While such a proposal is not acceptable for serious reasons, conceptual modelling is indeed facing a remarkable challenge in times of change. On the one hand, economics demand for reuse and interoperability, hence, for stable references. On the other hand, freezing structures is likely to compromise a software system's adaptability. Based on an analysis of this conflict and further challenges, it will be shown how languages for conceptual modelling can be designed to support both, the need for reference and the demand for change.

To support understanding and analysis of sustainability related aspects in organizations (e.g., via an assessment of a product’s life-cycle from the cradle to the grave), various instruments, among others, in the field of conceptual modeling, have been proposed. Although existing tools and languages are, to some extent, indeed supporting the product Life-Cycle Assessment (LCA), our investigations show that a hierarchy of Domain-Specific Modeling Languages(DSMLs) is needed to satisfy advanced requirements. In this paper, as an innovation for the field of LCA, we propose an application of multi-level language architecture to design a hierarchy of DSMLs encompassing concepts for LCAs that can be detailed to specific industrial domains and local needs of enterprises. This enables a new generation of instruments allowing users to use and refine concepts, corresponding to their specific needs.

Information technologies in general and artifical intelligence (AI) in particular try to shift operational task away from a human actor. Machine learning (ML) is a discipline within AI that deals with learning improvement based on data. Subsequently, retailing and wholesaling, which are known for their high proportion of human work and at the same time low profit margins, can be regarded as a natural fit for the application of AI and ML tools. This article examines the current prevalence of the use of machine learning in the industry. The paper uses two disparate approaches to identify the scientific and practical state-of-the-art within the domain: a literature review on the major scientific databases and an empirical study of the 10 largest international retail companies and their adoption of ML technologies in the domain are combined with each other. This text does not present a prototype using machine learning techniques. Instead of a consideration and comparison of the particular algorythms and approaches, the underling problems and operational tasks that are elementary for the specific domain are identified. Based on a comprehensive literature review the main problem types that ML can serve, and the associated ML techniques, are evaluated. An empirical study of the 10 largest retail companies and their ML adoption shows that the practical market adoption is highly variable. The pioneers have extensively integrated applications into everyday business, while others only show a small set of early prototypes. However, some others show neither active use nor efforts to apply such a technology. Following this, a structured approach is taken to analyze the value-adding core processes of retail companies. The current scientific and practical application scenarios and possibilities are illustrated in detail. In summary, there are numerous possible applications in all areas. In particular, in areas where future forecasts and predictions are needed (like marketing or replenishment), the use of ML today is both scientifically and practically highly developed.

Organizations and society nowadays face significant challenges. Organizations are required to fundamentally digital transform by assimilating Information Technology (IT) and Information System (IS) assets. Society faces an increasingly severe global climate disruption and needs to become more environmentally friendly. Green IT (GIT) and Green IS (GIS), as technologies and initiatives that seek to reduce the negative impacts of IT/IS on the environment, are a response to this. They can help organizations to gain a competitive advantage while also addressing broad-scale environmental issues. We undertake a literature review to frame the general GIT/GIS adoption process. We provide an overarching understanding by modeling a sequence of five cognitive adoption phases (outset, pre-adoption, adoption, post-adoption, and outcome) on four levels (environmental, societal, organizational, and individual). By recognizing that GIT/GIS adoption has multiple drivers and outcomes, we provide an extensive perspective on GIT/GIS adoption. 

Making informed decisions about historically grown and often complex business and Information Technology (IT) landscapes can be particularly difficult. Enterprise Architecture Management (EAM) addresses this issue by enabling stakeholders to base their decisions on relevant information about the organization’s current and future Enterprise Architectures (EAs). However, visualization of EA is often confronted with low usefulness perceptions. Informed by the cognitive fit theory (CFT), we argue that decision-makers benefit from interacting with EA visualizations using Augmented Reality (AR), because it enables a consistent task-related mental representation based on the natural use of decision-makers’ visual-spatial abilities. The goal of this paper is to demonstrate ARs suitability for EA-related decision-making. We follow the design science research (DSR) approach to develop and evaluate an AR head-mounted display (HMD) prototype, using the Microsoft HoloLens. Our results suggest that EA-related decision-making can profit from applying AR, but users find the handling of the HMD device cumbersome. 

Business process management (BPM) broadly covers a lifecycle of four distinct phases: design, configuration, enactment, and analysis and evaluation. Most BPM tool suites impose a strict separation between these phases, i.e., in each phase different languages and tools are used and the transition between phases is indirect and costly. This paper presents an environment for integrating all phases of the BPM lifecycle in which business process (BP) types and their instances can be modeled, visualized, managed and automatically synchronized, using a shared representation of models and code. The environment extends the capabilities of BP models to be used not only for specifying BPs but also for: (1) enactment—creating instance objects that capture BP operational data; (2) monitoring BP instances as they progress; (3) visualizing performance indicators of executed BPs at runtime; and (4) navigating from a BP type model to its respective instance population. As opposed to existing tools, the proposed environment does not require regenerating the workflow schema when BP designs change, nor does it require additional adaptations to support monitoring. Thereby, we facilitate a continuous and dynamic BPM environment, where workflow specifications can be changed at runtime. Our solution integrates a meta-programming language called eXecutable Modeling Facility (XMF) and the multi-perspective enterprise modeling framework (MEMO).

In this paper, we develop a new perspective on configuration processes inherent to smart service systems that brings human actors to the theoretical foreground, is informed by practice theory, and is grounded in an intervention study of smart locating systems used in home care of persons with dementia. Maintaining control of the location of persons with dementia is a major source of caregiver burden, and assistive technologies such as smart locating systems hold the promise of enhancing quality of life and reducing caregiver burden. Drawing from research on smart service systems, organizational configuration research, and practice theory, we articulate a conceptual model of configuring in practice to explain how practice elements and the capabilities of smart technologies become mutually configured. Our analysis of study participants’ experiences with the locating systems identified three distinctive configurations, characterized as enhanced smartness, degraded smartness, and fragile smartness, which developed through configuring processes. The configuring in practice model we develop here helps explain why unexpected and anticipated configurations develop and thus the conditions that facilitate or inhibit value cocreation in smart service systems.

Purpose The purpose of this paper is to include several studies that define different critical success factors (CSF) which have to be considered to support the implementation of technology-enhanced learning (TEL) approaches. An analysis of such studies revealed that regional differences seem to determine the CSF for TEL approaches, certain CSF are relevant for TEL approaches in general and professionals in higher education determine which influential factors they consider when implementing TEL approaches. Thus, the question arises: in general, which influential factors do professionals in Austrian and German institutions of higher education actually consider when implementing TEL approaches? Design/methodology/approach The study is a quantitative research approach based on survey data. Findings The results show that certain influential factors seem to be generally important, such as the factors of respecting learning success or motivation. However, the outcome of the study also indicated that different mo...

In aircraft ground handling, ramp agents manage the teams on the airport apron who prepare aircraft for the next takeoff. We examined the impact of using auditory and visual notification cues (NC) in an information system for supporting ramp agents, measuring the users’ situation awareness (SA), task performance, and perceived ease of use. Eighty-eight participants took part in a laboratory experiment and performed a realistic dispatching task of a ramp agent. Results showed that auditory cues facilitate superior SA compared with the application of visual cues or their absence. Our findings may serve as a foundation for future work aiming to design more effective notification systems to support SA.

The Flexible Meta Modelling and Execution Language (FMMLx ) is a multi-level language that allows to create executable models. It is implemented in the integrated meta-programming and meta-modelling environment Xmodeler. The Xmodeler is based on XCore, a recursive, reflexive meta-model that allows the defnition and implementation of classes on arbitrary classifcation levels. However, XCore does not allow to assign classifcation levels to classes. The FMMLx extends XCore with explicit classifcation levels and intrinsic features that allow for deferred instantiation. Like XCore, the FMMLx features a common representation of models and code. As a consequence, models can be executed without the need to transform them to code. The use of the FMMLx during the last fve years was promising, since it allows to clearly promote reuse and flexibility of modelling languages and software systems. Nevertheless, some of the assumptions its design was based on had to be challenged. In addition, the use of the language was compromised by various  limitations. Against this background, it was decided to develop a substantially revised version, the FMMLx 2.0. This report presents an analysis of requirements that form the foundation for the subsequent  specifcation of the new version. The report also presents a proposal for a technical terminology of multi-level modelling.

Dealing with ill-structured problems is a central responsibility of the manager operating in a business environment of complexity and ambiguity. To assist in problem structuring, a number of problem structuring methods have been developed in the field of operations research. But the modeling approaches incorporated in existing problem structuring methods lack semantic expressiveness, syntactical precision, and domain-specific modeling concepts. In contrast, the field of enterprise modeling offers a range of semantically rich domain-specific modeling languages. In this paper, we report on work towards a more expressive problem structuring method that integrates insights from theoretical problem solving research, core assumptions of the field of problem structuring methods, and modeling languages from the field of enterprise modeling. Specifically, we present results of a conceptual study of theoretical views of the concept of a problem, we present a meta model conceptualization of ‘problem’ in the context of enterprise modeling, and we illustrate the practical use of the proposed meta model with a case study. The presented conceptualization contributes to the field of enterprise modeling by offering a more nuanced ‘problem’ modeling concept than is currently available, and by constituting progress towards a problem structuring method that is more expressive and versatile than existing approaches.

Smart connected products (SCPs) have gained significant attention in different domains because they offer numerous benefits and change the way of competition and value creation. While quality is im-portant for SCPs, no holistic quality model is available to target the present quality problems. Further-more, since the concept of an SCP is quite abstract, a bottom-up approach that starts with a concrete example seems suitable. Therefore, this paper identifies the five key components of SCPs and maps them to self-tracking solutions (STS) in order to show that STSs are suitable substitutes. We also analyse quality models in corresponding areas to verify the absence of a holistic quality model for the selected example. This contribution identifies the research gap regarding holistic, stakeholder-oriented quality models and helps researchers understand SCPs better. 

This report documents the program and the outcomes of Dagstuhl Seminar 17492 "Multi-Level Modelling". This seminar brought together researchers and industry practitioners from the fields of conceptual modeling, ontologies, and formal foundations to discuss and share the benefits of Multi-Level Modelling (MLM), to develop an agreement on MLM terminology and scope, and to drive future research directions in MLM. Some foundational presentations were given by the seminar organizers to ground the discussions and provide an initial set of open questions which would lead to the formation of the working groups. In addition, six industry representatives gave talks explaining the needs, challenges, utility, and possible issues with adoption of MLM in industry. Based on the original seminar goals, the talks, and the resulting discussions, four working groups were established to investigate: the formal and ontological "Foundations"of MLM; promising "Applications" and potential evaluation criteria for MLM methods; the "Dynamic Aspects" of MLM, such as processes and behaviour; and, the use of and impact on "Model Transformations" in the context of MLM.

A central conflict in decision and problem solving support is known as the ‘Power/Generality’ trade-off. The incorporation of a high level of domain-specific concepts and mechanisms in a decision instrument will increase the instrument’s power but will do so at the cost of the instrument’s generality. This paper has two purposes. First, it brings to attention the power/generality conflict in conceptual decision and problem solving modeling, and it demonstrates the resultant problems in relation to an existing enterprise decision modeling language. Second, the paper proposes the use of a multi-level modeling paradigm as a possible resolution of the conflict, and it proposes concrete re-conceptualizations for an existing modeling language to alleviate the associated problems.

In this contribution, the experiences and results from the tests under real field conditions are described, which are concerned with grid automation systems in the research project Agent.HyGrid. Furthermore, the deployment of the grid automation system in a real-world distribution grid is discussed.
 

The last decade has seen a rise in software-based platforms that engender entirely new ecosystems. In newly emerging platform markets, platforms compete for partners and customers in a rapidly changing environment. Yet, extant research mostly studies platforms’ supply-side and demand-side strategies in relatively established platform markets. By combining a market-level and platform-level perspective, our research aims to develop a holistic understanding about the interdependencies between business model decisions, market evolution, and performance outcomes of platforms in emerging markets. We focus on the novel context of Massive Open Online Course (MOOC) platforms, analyzing longitudinal data for 35 MOOC platforms and their ecosystems. To account for the multi-level perspective, our research applies an innovative mixed-methods approach that combines qualitative methods with quantitative measures and visualizations derived from network analysis. Our findings suggest that platforms in new markets converge towards common business models as market leaders imitate the business model innovations of its smaller competitors to manifest their market position. Based on these analyses, we derive four propositions on how the dynamics of a platform’s business model and ecosystem position affect each other and the platform’s market performance.

Research on Shadow IT is facing a conceptual dilemma in cases where previously “covert” systems developed by business entities are integrated in the organizational IT management. These systems become visible, are thus not “in the shadows” anymore, and subsequently do not fit to existing definitions of Shadow IT. Practice shows that some information systems share characteristics of Shadow IT but are created openly in alignment with the IT organization. This paper proposes the term “Business-managed IT” to describe “overt” information systems developed or managed by business entities and distinguishes it from Shadow IT by illustrating case vignettes. Accordingly, our contribution is to suggest a concept and its delineation against other concepts. In this way, IS researchers interested in IT originated from or maintained by business entities can construct theories with a wider scope of application that are at the same time more specific to practical problems. In addition, the terminology allows to value potentially innovative developments by business entities more adequately.

ER 2017 Workshops AHA, MoBiD,
MREBA, OntoCom, and QMMQ
Valencia, Spain, November 6–9, 2017, Proceedings

To appear

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This work introduces the concept of testbed application of energy agents, which is the intermediate step between testing agents in pure simulation environment and deploying them in real energy distribution systems. In the testbed application case, the energy agent is taken from the simulation environment and deployed to dedicated hardware, where it controls a simulated or real technical system, while still working against a simulated environment. Compared to a pure simulation environment, this application case raises a number of new challenges, mainly resulting from inter-platform agent communication. In this work these challenges are discussed and an implementation handling them is presented and evaluated.
 

This volume consists of revised selected papers presented at the 3rd and 4th International Conference on Smart Energy Research, SmartER Europe 2016 and 2017, held in Essen, Germany, in February 2016 and 2017. The 13 full papers included in this volume were carefully reviewed and selected from 25 submissions. The papers discuss recent advances and experiences in building and using new IT-based solutions for Smart Grids and Smart Markets combining the knowledge of different disciplines such as engineering, business management and economics as well as computer science. They reflect the versatility and the complexity of the transformation process in the energy sector and also show the great need for research that is required to achieve the high targets for a digitized and sustainable energy landscape.
 

Today, value is co-created in sociotechnical systems in which different stakeholders integrate resources (products and services) in an interactive process. For these systems to be successful, quality is very important. However, existing systems often fail to deliver the right level of quality, and the available quality approaches seem to be insufficient. Therefore, this paper provides insight into the role of quality by applying a service system perspective. We show that a holistic quality perception that reflects the modern expectations of stakeholders is necessary. In addition, different resources for modern services and their interaction need to be taken into account. This results in the need for quality management specific for sociotechnical systems, which integrates different existing approaches to cover these demands. Furthermore, the authors suggest future research on perceived quality and technical support in this context.

A simple idea underpins the scientific process: All results should be subject to continued testing and questioning. Given the particularities of our international IS discipline, different viewpoints seem to be required to develop a picture of the merits and limits of testing and replication. Hence, the authors of this paper approach the topic from different perspectives. Following the ongoing discourse in neighbouring disciplines, we start by highlighting the significance of testing, replication and negation for scientific discourse as well as for the sponsors of research initiatives. Next, we discuss types of replication research and the challenges associated with each. In the third section, challenging questions are raised in the light of the ability of IS research for self-correction. Then, we address publication issues related to types of replications that require shifting editorial behaviors. The fifth section reflects on the possible use and interpretation of replication results in the light of contingency. As a key takeaway, the paper suggests ways to identify studies worth replicating in our field and reflects on possible roles of replication and testing for future IS research.

Based on a critical account of the dominant concept of theory, the paper presents an alterna-tive, wider notion of theory. It is motivated by the need to cope with a contingent research subject and the assumption that IS should provide an orientation for managing the digital transfor-mation. Unlike neo-positivistic notions of theory, the proposed conception is not restricted to de-scriptions of the factual, but may be aimed at de-signing possible future worlds. Conceiving of possible future worlds requires overcoming the barriers created by language that constitutes our idea of the present world. The paper discusses the resulting methodological challenges and outlines how they might be addressed.

Service-dominant logic highlights the ability of service ecosystems to ’self-adjust’ as a reaction to sys-temic inefficiencies or external changes [1]–[3]. We contribute to the question on how focal actors shape the boundaries of service ecosystems through service innovation. This is a single case study on a digital eco-system focused on a first mover in digital platforms for Massive Open Online Courses (MOOCs): Udacity. We found two mechanisms, where Udacity shaped the boundaries of its ecosystem: ’user self-service integra-tion’ and ’gradual partner disintegration’. Through-out three phases between 2011 and 2015 they disinte-grated services from higher education, namely offer-ing courses online, designing course, and accredita-tion due to lowly perceived adaptability of universities and external pressures for finding a sustainable busi-ness model. Additionally, they disintegrated self-orga-nized solutions of user needs and re-integrated them with new actors. This led to newly shaped boundaries of the service ecosystem.

Drawing on notions of power and the social construction of risk, we build new theory to understand the persistence of shadow systems in organizations. From a single case study in a mid-sized savings bank, we derive two feedback cycles that concern shifting power relations between business units and central IT associated with shadow systems. A distant business-IT relationship and changing business needs can create repeated cost and time pressures that make business units draw on shadow systems. The perception of risk can trigger an opposing power shift back through the decommissioning and recentralization of shadow systems. However, empirical findings suggest that the weakening tendency of formal risk-management programs may not be sufficient to stop the shadow systems cycle spinning if they fail to address the underlying causes for the emergence of shadow systems. These findings highlight long-term dynamics associated with shadow systems and pose “risk” as a power-shifting construct.

In this paper, we problematize a relative absence of established ways to develop and communicate knowledge contributions (KC) from Design-oriented research (DOR) within information systems. This is problematic since it hinders the potential for knowledge accumulation within the field. Thus, for communicating KC, we propose a framework, dubbed PDSA (Prescriptive, Descriptive, Situated, and Abstract). To develop KC especially from empirical data, we suggest the use of qualitative process methods. The framework is illustrated by revisiting a published DOR study. Finally, we show how the PDSA framework serves as a template to establish firm KC in DOR. In addition, we explore contributions generated from empirical data and suggest possibilities to use qualitative process methods as means to increase transparency and rigor of KC development and communication.

The current transformation process of how energy is supplied attracts great interest from many different market players. As a consequence, many proprietary solutions for ``smart'' energy applications are flooding the market. This turns out to be rather a problem than part of the solution for the systematic development of future energy grids. Additionally, the absence of necessary standards blocks further developments that enable the creation of novel, market-driven and hybrid control solutions. To overcome these problems, we suggest a standardized control approach for hybrid energy systems by means of a so called Energy Option Model (EOM). This unifying model and the therewith developed decision support system provides the necessary technical understanding and the economic assessment options for network-connected energy conversion systems. Thus, it can be used for single on-site systems as well as for aggregated systems that are controlled in centralized or decentralized manner. This paper presents and discusses exemplary use cases for our EOM that illustrate the centralized as well as the decentralized use of our approach within hybrid energy systems. Overall, we believe that the EOM represents the key approach for a further systematic development of an open hybrid energy grid.

In this book, Prof. Ahlemann and Prof. Nils Urbach discuss the implications of the current need for digitalization for companies and their IT. In the course of digitalization, IT organizations’ focus shifts from being a mere service provider to supporting the shaping of the business. IT is consequently increasingly required to cooperate proactively with other departments and to identify innovation possibilities.

The book’s target group includes IT managers, executives responsible for IT, and practice-oriented researchers, providing advice on how to react to, but also shape digital transformation.

In recent years, several developments in the energy sector have been imposing major challenges on our energy supply infrastructure. Due to the liberalization of the energy markets that started in the 1990s, longstanding monopolies are being broken up and new actors enter the stage. An increasing awareness regarding the environmental impacts of fossil fuel-based electricity generation put renewable energy sources like wind and solar on a lasting growth path. The volatility inherent to these sources and the shift from centralized to decentralized generation necessitate new approaches as to how energy is marketed, distributed and consumed. The smart grid, i.e. equipping the energy infrastructure with modern information and communication technology, is widely considered essential in addressing the challenges outlined.
 

As a result of fast growing share of renewable energy production in the energy market the management of power and its distribution becomes more and more complex. The here presented Energy Option Model (EOM) seems to be a promising solution to handle this newly arisen complexity. This paper will present the EOM and analyze its capabilities in centralized evaluation of aggregated systems. The example use-case will be the charging process of a fleet of electric vehicles. While the results support the potential of the EOM to implement coordination strategies for aggregations of systems, they also show the general limitations of centralized control solutions for larger groups of systems in the context of smart grids.

Die gegenwärtigen Entwicklungen in Wirtschaft, Gesellschaft und Informationstechnologie führen zu veränderten Anforderungen an den modernen Wissensarbeitsplatz. Um diesen Anforderungen gerecht zu werden, sind die erforderlichen organisationalen und technologischen Voraussetzungen zu schaffen. Der vorliegende Beitrag geht der Frage nach, welche konkreten Anforderungen an den „Wissensarbeitsplatzplatz der Zukunft“ gestellt werden, welche Herausforderungen sich dadurch für das strategische IT-Management ergeben und wie die erforderlichen Entwicklungsschritte aktiv angegangen werden können. 

Bookstores have been strongly affected by the rise of electronic commerce. Traditional (physical) bookstores now have to compete with online counterparts that possess several advantages over them, such as lower prices and 24/7 availability. This paper investigates the influence that online bookstores have on the sales of physical bookstores in China. The geographic restriction is based on the particularities of the Chinese market that differentiate China from other markets, both in the book market as well as in the adoption of E-commerce. Since there is a lack of overview in the English academic literature on this topic, we conducted a literature review to summarize the current state of research. Our research highlights multiple advantages and disadvantages of physical and online bookstores in the Chinese market, which in turn influence the sales of traditional bookstores. This paper offers a theoretical and a practical contribution. Participants of the Chinese book market can use the results to better assess and improve their market position by addressing the disadvantages or building on the strengths identified during the review. Furthermore, this paper can serve as a starting point for English researchers, as almost no research on this topic has been published in English.

Adaptation models; Agent.HyGrid project; Computational modeling; Context; Control Engineering; decentralized decision making; electrical power; energy markets; future energy grids exhibit; hybrid hardware test-beds; hybrid power systems; hybrid software test-beds; multiagent systems; multi-agent systems; multienergy infrastructure testing; power engineering computing; power markets; program testing; Simulation; Software; software artifacts; software development processes; software reusability; Systematics; Testing

Zusammenfassung Das gemeinsame Schreiben in kurzen Zeiträumen in sogenannten Booksprints hat vor allem durch digitale Technologien an Fahrt gewonnen. Plattformen zur virtuellen Kooperation und Kommunikation sowie schließlich auch zur Online-Veröffentlichung ermöglichen einen gemeinsamen, räumlich verteil-ten und parallelisierten Veröffentlichungsprozess, welcher Absprachen und Übergänge teils drastisch verkürzt. Gerade im Bereich der Hochschulen gibt es jedoch nur wenige Beispiele für Booksprints. In der folgenden vergleichen-den Fallstudie werden drei erfolgreiche Beispiele miteinander verglichen: eine beim E-Learning-Tag in Koblenz in drei Stunden erstellte Textsammlung zu persönlichen Erinnerungen an Lieblings-Lernmedien (Auwärter u.a., 2013), die Überarbeitung des Lehrbuchs Lernen und Lehren mit Technologien in sieben Tagen, an dem sich mehr als 250 Mitwirkende beteiligten (L3T 2.0, Ebner \\\& Schön, 2013) sowie ein dreitägiger Booksprint mit der Sammlung von innovativen Fallbeispielen zu neuartigen Geschäftsmodellen des Hochschulforums Digitalisierung (Bremer u.a., 2015). Eine Darstellung der Lessons Learned bzw. Empfehlungen für Nachahmer/innen schließt den Beitrag ab.

A crucial factor of improving IT-based services lies within the boundaries of understanding its usage. This is especially true for highly integrated services, like educational service (Shostack 1982), as value co-creation is based upon usage processes (Prahalad and Ramaswamy 2004; Vargo and Lusch 2004). Usage can be assumed as a process of (autonomous) resource integration between several actors. Therefore, Lusch and Vargo (2014) draw on relatively self-contained, and self-adjusting systems” (p. 161), they call service ecosystems. Self-containment and self-adjustment are a result of inherent self-supporting and loosely-coupled actors, who mainly share two things: (1) a will to co-create value, and (2) institutional logics, like rules and standards, which mediate their actors coupling. As each actor in a service ecosystem chooses on its own, which resources it integrates into value-co-creation, the number and type of actors become may become less pre-determined and less expectable for focal service suppliers. We choose to take a traditional supplier-perspective and ask: How do resource-integrating users autonomously – and therefore unexpectedly – integrate actors into value co-creation processes?

We draw on notions of power and the social construction of risk to understand the persistence of shadow IT within organizations. From a single case study in a mid-sized savings bank we derive two feedback cycles that concern shifting power relations between business units and central IT associated with shadow IT. A distant business-IT relationship, a lack of IT business knowledge and changing business needs can create repeated cost and time pressures that make business units draw on shadow IT. The perception of risk can trigger an opposing power shift back through the decommissioning and recentralization of shadow IT. However, empirical findings suggest that the weakening tendency of formal programs may not be sufficient to stop the shadow IT cycle spinning if they fail to address the underlying causes for the shadow IT emergence. These findings highlight long-term dynamics associated with shadow IT and pose risk as a power-shifting construct.

The ongoing conversion of our energy supply encounters a great interest of many different market players that were originally located in different industries. As a consequence, a vast amount of proprietary solutions for “smart” energy applications is flooding the market. This tends to be rather a problem than part of the solution for the systematic development of future energy grids. Here, the absence of necessary unifications and standards blocks further developments that would enable the creation of novel, market-driven and hybrid control solutions for various types of technical systems. To overcome these problems, we present in this article our notion and the definition of a unified autonomous software entity that we call Energy Agent. Based on the energy conservation law and a generalized energy option model, we claim that our Energy Agent approach has the capabilities to enable cross domain interactions between different types of energy systems and networks. Further we will outline a systematic development process for Energy Agents that considers implementation, simulation, test-bed application and a real on-site usage. By taking into account these development stages, we expect to concurrently develop a novel laboratory that enables to competitively test and validate new and hybrid control solutions before they are applied in real systems.
 

This chapter presents a novel approach to dynamic resource allocation in hybrid energy grid scenarios, called energy-agents. This concept allows the easy control of inter-domain energy exchanges, such as heat generation from electricity or gas, the production of gas from electricity, or vice versa, based on the first law of thermodynamics. In a first hardware and software implementation, we were able to showcase the functionality and usability of this approach, enabling the developers of smart grid solutions to use the same code throughout the entire development process. This reusability will help to keep down development time and costs. On top of this, we were able to realize energy and cost savings by dynamically allocating the energy sources, as required by the consumer processes.
 

Die sich stets weiter entwickelnden Informations- und Kommunikationstechnologien (IuK) sind Treiber eines beispiellosen Strukturwandels: Sie durchdringen und prägen zunehmend unsere Kommunikation, wirtschaftliches Handeln und soziale Interaktionen. Auch im schulischen Bildungssystem muss man sich daher mit der Frage auseinandersetzen, welche Rolle IuK im praktischen Unterricht und in den schulischen Bildungsinhalten spielen sollte. Vor diesem Hintergrund bietet der vorliegende Arbeitsbericht eine umfassende Analyse der verschiedenen Facetten von IuK im Kontext allgemeinbildender Schulen. Dazu wird zunächst ein Strukturierungsrahmen für schulische IuK-Bildungsinhalte entwickelt. Desweiteren erfolgt eine umfassende Auswertung bisheriger empirischer Studien und Literaturquellen. Die Analyse fokussiert dabei auf die aktuelle Rolle von IuK-Ressourcen und -Bildungsinhalten an deutschen Schulen und ergänzt dieses Bild – wo möglich – durch einen Vergleich mit anderen Industrienationen. Abschließend werden allgemeine Empfehlungen zur Ausrichtung der IuK-Bildung an Schulen abgeleitet und Forschungsbedarfe aufgezeigt.

Dieses Buch führt in den Bereich der Dienstleistungsinnovation ein und stellt mit der Quadromo-Methode einen praxistauglichen Ansatz für das Service Design vor. Zahlreiche Anwendungsbeispiele aus der betrieblichen Praxis zeigen, wie sich Prozessgestaltung und Geschäftsmodellinnovation ergänzen und verbinden lassen. Checklisten und Umsetzungstipps unterstützen die erfolgreiche Realisierung von Dienstleistungsinnovationen mit der Quadromo-Methode im Unternehmen.

Business process management (BPM) is a topic that has received immense attention in information systems research and practice. While the existing literature comprehensively covers BPM methods, techniques, and tools, the development of BPM capability in organizations remains under-researched. Existing studies mainly present maturity models with generic sequences of distinct stages that provide a rather simplistic perspective on BPM capability progress. Taking a process theory view and drawing from organizational change literature, we elaborate on alternate templates for explaining BPM capability development. By revisiting two case studies on BPM capability development, we analyze the explanatory power of four basic theories of capability development and thus advance existing approaches to explain BPM capability progress. Our analysis shows the general applicability of these theories and points to particular advantages, disadvantages, and application conditions. Using the four basic theories as alternate templates, we also offer a much more-detailed explanation of the mechanisms behind the episodes of BPM capability progress that we observed in the two case studies. In particular, the different theoretical templates allow one to better understand the influence of internal and external contexts on BPM capability progress.

Vor dem Hintergrund des durch Informationstechnologien (IT)angestoßenen weitreichenden Transformationsprozesses in allen sozialen, gesellschaftlichen und wirtschaftlichen Be-reichen erläutert der Forschungsberichtdie Relevanz der Wirtschaftsinformatik für die schulische Bildung. Nach der grundlegenden Beschreibung des Gegenstandsbereichs der Wirtschaftsinformatik werden wesentlicheAnforderungen an die Vermittlung von Wirtschaftsinformatik-Themen im schulischen Bereich abgeleitet.Für ein Fach Wirtschaftsinformatik liegen in Nordrhein-Westfalenbislang nur an beruflichen Schulen Lehrpläne vor.Die Ergebnisse einer ersten Lehrplananalyse weisenauf deutliche Schwächenhinsichtlich der Abbildung von Wirtschaftsinformatikkonzepten und -methoden in den entsprechenden Fächern hin. Eineangemessene Vermittlung setzt zunächst die adäquate Ausbildung der Lehrenden voraus. Der Bericht bietet dazu eine Analyse der Lehramtsstudiengänge mit beruflicher Fachrichtung „Wirtschaftsinformatik“. Abschließend werden Maßnahmen vorgeschlagen, die aus fachlicher Sicht geeignet erscheinen daraufhinzuwirken, dass die Themen der Wirtschaftsinformatik zukünftig in den Lehrplänen der (beruflichen) Schulen und in der Lehrerausbildung adäquater abgebildet werden