Process mining research has made tremendous progress in analyzing, visualizing, and predicting the performance of business processes through computational techniques. However, little attention has been brought to understanding why and how business processes behave as they do. Process mining results alone are not sufficient to arrive at meaningful interpretations about the dynamics and changes of a given business process. Rather, we need to account for contextual factors that underlie and explain the behavior of processes. In this paper, we make two central contributions. First, we develop a framework that depicts relevant factors to make sense of process mining results. The framework is intended to help researchers and practitioners explain why and how processes change across a variety of contexts. Second, we demonstrate the application of our framework within a real-world case: a customer onboarding process in a European financial institution.

The amount of battery-powered Internet of Things (IoT) devices is strongly increasing. Predicting their battery health is important to maintain and proactively replace them to avoid outages. This article gives an overview of the existing literature using the IoT functionality to track and predict battery health. We elaborate on battery health concepts commonly found in the literature, i.e., State of Charge (SoC), State of Health (SoH), and remaining useful life (RuL). We provide definitions, use cases, and examples synthesized from a final selection of 23 reviewed papers. Important components are identified and assessed on how best to combine such components to build a state-of-the-art battery health tracking platform. The acquisition sensors send information about the battery to the IoT-connected controller for preprocessing. The aggregated data is then sent via wireless networking to a cloud-based monitoring platform, where it is stored in a database system. It can be visualized to the customer via a visualization interface.

Small devices, such as drills, are increasingly being equipped with Internet of Things (IoT) functions that make it possible to collect usage data, adapt the way they work, and also gain insights into the further development of the devices; even in application areas with limited battery capacity and noncontinuous Internet connection. Since the health of the battery is a crucial factor in the successful long-term deployment of these IoT devices, tracking their capacity-based State of Health (SoH-C) is important to avoid outages. To preserve energy, utilization data is aggregated and sent when an event occurs (e.g., charging). To avoid the need to introduce expensive intrinsic battery tracking sensors as done in large-scale IoT devices, this article uses the existing capacity tracking sensor of the battery management system (BMS) to track the SoH by applying the peak State-of-Charge (SoC) extraction technique. However, an SoH update can only be achieved and verified when the battery is peak cycled; which does not happen every charge/discharge cycle and also depends on the charging behavior of the customer. As long as the battery is shallow cycled, existing approaches would not update the SoH. To ensure continuous SoH tracking, the novel solution, presented in this article, called “battery health index” (BHI) combines physical capacity-based measurements with data-driven machine learning predictions based on utilization data to provide an always up-to-date SoH. The proposed state-of-the-art method is evaluated on a hand-held battery platform with millions of batteries and it outperforms existing solutions. The presented model enables proactive battery exchange by predicting the remaining useful lifetime (RUL) therefore increasing customer experience.

An increasing presence of practitioners with doctoral degrees in Information Systems and related disciplines holds promise to advance Information Systems research. The prospect is to gain more knowledge from the practical experience of developing, using, and managing information systems in context. To scientifically capitalise on this opportunity, this EJIS special issue introduces the research genre of “Information Systems Clinical Research”. The genre presents knowledge generated from practitioner-researcher interventions to achieve desired outcomes in information systems development, use, and management practice contexts. In this editorial, we introduce and conceptualise the genre; we present a research framework that defines its four key elements; and we discuss how to address its key challenges in research projects. As a result, we derive ten criteria for rigorous Information Systems Clinical Research and provide examples on how the articles published in the special issue have addressed these criteria. We conclude with a call to further advance clinical research as an important part of the Information Systems discipline.

While the potential of deep learning(DL) for automating simple tasks is already well explored, recent research started investigating the use of deep learning for creative design, both for complete artifact creation and supporting humans in the creation process. In this paper, we use insights from computational creativity to conceptualize and assess current applications of generative deep learning in creative domains identified in a literature review. We highlight parallels between current systems and different models of human creativity as well as their shortcomings. While deep learning yields results of high value, such as high quality images, their novelity is typically limited due to multiple reasons such a being tied to a conceptual space defined by training data and humans. Current DL methods also do not allow for changes in the internal problem representation and they lack the capability to identify connections across highly different domains, both of which are seen as major drivers of human creativity.

Visual realism in Virtual Reality (VR) increases both immersion and development costs. Consequently, it is important to understand the cost-benefit trade-off of specific aspects of visual realism. Determining the extent of visual realism often leads to decisions on the level of visual complexity of a Virtual Environment (VE). In this paper, we investigate the impact of visual complexity on a user's spatial orientation through a user study. To do so, we created a VE containing parts of a real-world place. Participants were asked to map their location within the VE to the corresponding real-world location. They were provided by a pop-up map of the entire VE, on which they were required to choose one named location out of a predefined set of locations. We manipulated the VE's visual complexity by varying the visual elements used to provide cartographic information, namely a map overlay and 3D blocks as buildings. This results in four scene types: i) landscape contour, ii) landscape contour with 3D buildings, iii) landscape contour overlaid with a map, and iv) landscape contour with both 3D buildings and the map overlay. Each participant performed our location recall task for each scene type. Our findings provide empirical evidence that addition of each of these two visual elements individually improved spatial orientation, while their combination only adds a slight improvement.

On the 10th anniversary of the NeuroIS field, we reflect on accomplishments but, more importantly, on the future of the field. This commentary presents our thoughts on a future NeuroIS research agenda with the potential for high impact societal contributions. Four key areas for future information systems (IS) research are: (1) IS design, (2) IS use, (3) emotion research, and (4) neuro-adaptive systems. We reflect on the challenges of each area and provide specific research questions that serve as important directions for advancing the NeuroIS field. The research agenda supports fellow researchers in planning, conducting, publishing, and reviewing high impact studies that leverage the potential of neuroscience knowledge and tools to further information systems research.

Regulations to contain the spread of COVID-19 have affected corporations, institutions, and individuals to a degree that most people have never seen before. Information systems researchers have initiated a discourse on information technology’s role in helping people manage this situation. This study informs and substantiates this discourse based on an analysis of a rich dataset: Starting in March 2020, we collected about 3 million tweets that document people’s use of web-conferencing systems (WCS) like Zoom during the COVID-19 crisis. Applying text-mining techniques to Twitter data and drawing on affordance theory, we derive five affordances of and five constraints to the use of WCS during the crisis. Based on our analysis, our argument is that WCS emerged as a social technology that led to a new virtual togetherness by facilitating access to everyday activities and contacts that were “locked away” because of COVID-19-mitigation efforts. We find that WCS facilitated encounters that could not have taken place otherwise and that WCS use led to a unique blending of various aspects of people’s lives. Using our analysis, we derive implications and directions for future research to address existing constraints and realise the potentials of this period of forced digitalisation.

There is a significant shortage of expert Information Technology (IT) personnel in Europe and elsewhere and a marked under-representation of women in the field. This paper identifies important gaps in research on gender imbalance in the IT profession and motivates future Information Systems research to address each of them. First among these gaps is the lack of research on the far-reaching consequences of gender imbalance in the IT profession. Second, despite a considerable body of research, there is the lack of coherent explanation for this imbalance. Third, although many intervention programmes have been implemented in this area, gender diversity in practice has not improved significantly. This research field also requires theorisation based on the cumulative research efforts in the field, comparative studies in various contexts, and longitudinal studies. We point to opportunities to investigate each of these issues and recommend directions for future research and actionable research questions.

Since its inception, the editors of the European Journal of Information Systems (EJIS) have been determined to make it a place for interesting discussions of research about meaningful problems – di...

This essay discusses the use of big data analytics (BDA) as a strategy of enquiry for advancing information systems (IS) research. In broad terms, we understand BDA as the statistical modelling of large, diverse, and dynamic data sets of user-generated content and digital traces. BDA, as a new paradigm for utilising big data sources and advanced analytics, has already found its way into some social science disciplines. Sociology and economics are two examples that have successfully harnessed BDA for scientific enquiry. Often, BDA draws on methodologies and tools that are unfamiliar for some IS researchers (e.g., predictive modelling, natural language processing). Following the phases of a typical research process, this article is set out to dissect BDA’s challenges and promises for IS research, and illustrates them by means of an exemplary study about predicting the helpfulness of 1.3 million online customer reviews. In order to assist IS researchers in planning, executing, and interpreting their own studies, and evaluating the studies of others, we propose an initial set of guidelines for conducting rigorous BDA studies in IS.

Design science has evolved as a major research paradigm in the information systems (IS) discipline, which aims to design innovative and useful IT artifacts, such as conceptual models and software systems. Despite the increasing attention paid to the cognitive and emotional mechanisms that underlie the perception of such artifacts, research that explores the neurobiological determinants of these mechanisms has only recently begun to emerge. The primary argument for the use of neurobiological approaches in IS design science research is that IT artifact design — and, ultimately, human-computer interaction in general — may significantly benefit from neuroscience theories, concepts, methods, and data. In particular, the consideration of neuroscience may improve IT artifacts' alignment with users' perceptual and information processing mechanisms, particularly the brain. Against this background, this article presents a taxonomy of application strategies for neuroscience in IS design science research. It describes three major areas of application and explains that conducting research in an area comes with a specific set of requirements (e.g., applicability, costs, accessibility, and knowledge relevant to planning and conducting a research project). Therefore, if an IS design science scholar decides to draw upon neuroscience, the taxonomy transparently explains possible working areas and corresponding requirements. The taxonomy is described based on example studies published in the IS literature and on contributions that appeared in outlets pertaining to related disciplines, such as affective computing and neuroergonomics. The article concludes that, if neuroscience is considered a valuable complement to the more traditional approaches, it has the potential to become a major reference discipline for IS design science research.

Topical developments in software-engineering facilitate the establishment of new design patterns for information systems. In Service-Oriented Architectures (SOA), processes of an information system can be extracted and "out-tasked" to service providers. KEEN/MCDONALD highlight the changes that are brought about by such an architecture with their statement ,,Out- tasking [...] breaks a company into a portfolio of process-centered operations rather than interlocking departments or functions." [30]. Examples of technologies that have been developed for this purpose are COM+, CORBA und RMI [55]. With the initiative of Enterprise Application Integration (EAI), web-services turn out in practice to enable a widely spread realization of SOA.