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Owing to advancements in artificial intelligence (AI) and specifically in machine learning, information technology (IT) systems can support humans in an increasing number of tasks. Yet, previous research indicates that people often prefer human support to support by an IT system, even if the latter provides superior performance – a phenomenon called algorithm aversion. A possible cause of algorithm aversion put forward in literature is that users lose trust in IT systems they become familiar with and perceive to err, for example, making forecasts that turn out to deviate from the actual value. Therefore, this paper evaluates the effectiveness of demonstrating an AI-based system’s ability to learn as a potential countermeasure against algorithm aversion in an incentive-compatible online experiment. The experiment reveals how the nature of an erring advisor (i.e., human vs. algorithmic), its familiarity to the user (i.e., unfamiliar vs. familiar), and its ability to learn (i.e., non-learning vs. learning) influence a decision maker’s reliance on the advisor’s judgement for an objective and non-personal decision task. The results reveal no difference in the reliance on unfamiliar human and algorithmic advisors, but differences in the reliance on familiar human and algorithmic advisors that err. Demonstrating an advisor’s ability to learn, however, offsets the effect of familiarity. Therefore, this study contributes to an enhanced understanding of algorithm aversion and is one of the first to examine how users perceive whether an IT system is able to learn. The findings provide theoretical and practical implications for the employment and design of AI-based systems.

Process mining is an active research domain and has been applied to understand and improve business processes. While significant research has been conducted on the development and improvement of algorithms, evidence on the application of process mining in organizations has been far more limited. In particular, there is limited understanding of the opportunities and challenges of using process mining in organizations. Such an understanding has the potential to guide research by highlighting barriers for process mining adoption and, thus, can contribute to successful process mining initiatives in practice. In this respect, the paper provides a holistic view of opportunities and challenges for process mining in organizations identified in a Delphi study with 40 international experts from academia and industry. Besides proposing a set of 30 opportunities and 32 challenges, the paper conveys insights into the comparative relevance of individual items, as well as differences in the perceived relevance between academics and practitioners. Therefore, the study contributes to the future development of process mining, both as a research field and regarding its application in organizations.

The research field of Business Process Management (BPM) has gradually developed as a discipline situated within the computer, management and information systems sciences. Its evolution has been shaped by its own conference series, the BPM conference. Still, as with any other academic discipline, debates accrue and persist, which target the identity as well as the quality and maturity of the BPM field. In this paper, we contribute to the debate on the identity and progress of the BPM conference research community through an analysis of the BPM conference proceedings. We develop an understanding of signs of progress of research presented at this conference, where, how, and why papers in this conference have had an impact, and the most appropriate formats for disseminating influential research in this conference. Based on our findings from this analysis, we provide conclusions about the state of the conference series and develop a set of recommendations to further develop the conference community in terms of research maturity, methodological advance, quality, impact, and progression.

The management and improvement of business processes are a core topic of the information systems discipline. The persistent demand in corporations within all industry sectors for increased operational efficiency and innovation, an emerging set of established and evaluated methods, tools, and techniques as well as the quickly growing body of academic and professional knowledge are indicative for the standing that Business Process Management (BPM) has nowadays. During the last decades, intensive research has been conducted with respect to the design, implementation, execution, and monitoring of business processes. Comparatively low attention, however, has been paid to questions related to organizational issues such as the adoption, usage, implications, and overall success of BPM approaches, technologies, and initiatives. This research gap motivated us to edit a corresponding special focus issue for the journal BISE/WIRTSCHAFTSINFORMATIK. We are happy that we are able to present a selection of three research papers and a state-of-the-art paper in the scientific section of the issue at hand. As these papers differ in the topics they investigate, the research method they apply, and the theoretical foundations they build on, the diversity within the BPM field becomes evident. The academic papers are complemented by an interview with Phil Gilbert, IBM’s Vice President for Business Process and Decision Management, who reflects on the relationship between business processes and the data flowing through them, the need to establish a process context for decision making, and the calibration of BPM efforts toward executives who see processes as a means to an end, rather than a first-order concept in its own right.

Investment advisory services of financial service providers (FSPs) exhibit several characteristics that are detrimental to advisory quality. The interaction of advisor and client is strained by a lack of transparency regarding the advisory process (what activities are performed and why) and the information used therein (what information is used for what purpose and with what effect), as well as regarding the precise costs of the service and the recommended products. In prior research, we suggested that process and information transparency issues may be appropriately addressed with collaborative information technology (IT) artifacts. In this paper, we argue that collaborative, transparent artifacts may also be a premise of enabling cost transparency. To this end, we describe a complete research cycle of designing, implementing and evaluating a shared cost-transparent IT artifact to support client-advisor interaction in investment advisory encounters. Evaluation results suggest the efficacy of our design in improving the clients’ perceived cost transparency as well as increase their satisfaction and their willingness to pay for the received investment advice. These findings may also challenge the common belief of FSPs that transparent, fee-based advisory services would neither be accepted by clients nor be economically viable. Practical implications of these findings for designing advisory encounters with supportive IT are discussed.

The concept ambient intelligence was first introduced more than ten years ago by the EU Information Society Technologies Advisory Group (ISTAG 1999). The result was a visionary description of a technological development in which information and communication systems are embedded in the user environment and enable numerous ways of individual support from the background. Until now, the term has played a secondary role in the German-speaking research community of business and information systems engineering (BISE). Instead, synonymous terms like pervasive computing or ubiquitous computing have been used (cf. e.g. Mattern 2001). The journal it – Information Technology was the first to dedicate an exclusive issue to the topic in a special issue (n.a. 2008). Moreover, some papers in the context of sub conferences as part of the Multi-Conference on Information Systems (MKWI) dealt with and identified ambient intelligence. Furthermore, the use of the concept, which has become known as “Ambient Assisted Living (AAL)”, is presently on the increase. One possible explanation for the more frequent use is the link with various AAL-related initiatives and their respective funding programs at both the federal and the EU level.

Data warehouse projects, today, are in an ambivalent situation. On the one hand, data warehouses are critical for a company’s success and various methodological and technological tools are sophisticatedly developed to implement them. On the other hand, a significant amount of data warehouse projects fails due to non-technical reasons such as insufficient management support or in-corporative employees. But management support and user participation can be increased dramatically with specification methods that are understandable to these user groups. This paper aims at overcoming possible non-technical failure reasons by introducing a user-adequate specification approach within the field of management information systems.