Resolving Inconsistencies in Declarative Process Models based on Culpability Measurement

Contrary to traditional process models, declarative process models define a set of declarative constraints to specify the behavior which a process should adhere to. In the scope of process mining, declarative process discovery aims to derive such constraint sets from event logs. Here, a problem for current discovery techniques is that of inconsistency. That is, dependent of certain event log characteristics, the derived constraint set may contain contradictory constraints. This in turn however makes the discovered model unusable, as contradictory constraints make it impossible to execute declarative process models, thus hampering previous process discovery efforts. In this work, we present an approach for resolving inconsistencies in declarative process models, based on methods from the scientific field of inconsistency measurement. We introduce our approach algorithm and evaluate its feasibility with data sets of the BPI Challenge 2017

User Experience Design and Digital Nudging in a Decision Making Process

When using online nudges to steer people in the right direction while they are making a decision, there is usually one preferable outcome. What might happen if the user experience is inadequate, will the nudges still work or might they be undermined? In this paper we investigate the correlation between user experience and digital nudges in a decision making process. A user A/B test was conducted to investigate the problem. The test participants visited one of two websites that included the same nudges where they were nudged to choose option (a) instead of (b). The only difference in the websites was the quality of the user experience, one website design had a good user experience while the other one offered an inadequate user experience. The results showed that everyone who was assigned the good user experience chose (a), while two of the inadequate experience participants chose (b). The results indicate that user experience design can be used for digital nudging

A Tool to Model and Simulate Dynamic Business Models

Software tools hold great promise to support the modeling, analyzing, and innovation of business models. Current tools only focus on the design of business models and do not incorporate the complexity of existing interdependencies between business model components. These tools merely allow simulating inherent dynamics within the models or different strategic decision scenarios. In this research, we use design science research to develop a prototype that is capable of modeling and simulating dynamic business models. We use system dynamics as a simulation approach and containers to allow deployment as web applications. This paper represents the first of three design cycles, realizing six out of 59 requirements that are collected from the literature on software tools for business models. We contribute toward the design of novel artifacts for business model innovation as well as their evaluation. Future research can use these results to build tools that consider and address the complexity of business models. Lastly, we present several options for extending the proposed tool in the future

The Good, the Bad, and the Dynamic: Changes to Retail Business Models During COVID-19

Crises, such as the COVID-19 pandemic, challenge the economy and require firms to become resilient to external change. During COVID-19, the retail industry faced doubleedged consequences. While brick and mortar business models (BMs) were discontinued, online retail thrived. Extant BM research has investigated several crises; however, it still lacks an explanation of how BM change increases resilience to cope with crises. We analyze the BMs of 45 European retailers and the BM changes implemented during the COVID-19 pandemic and their influence on the retailers\u27 revenue. We identify three types of retailers implementing different strategies to cope with the crises: the »good,« the »bad,« and the »dynamic.« These represent resilient BMs, un-resilient BMs, and BMs becoming resilient enabled by digital technology. We show how BM change creates resilience and performance benefits. For practice, we show how retailers adapted their BM to a crisis leveraging digital technology

Towards a Conceptualization of Capabilities for Innovating Business Models in the Industrial Internet of Things

The emergence of Internet of Things (IoT) technologies offers promising value potentials for industrial manufacturers based on the combination of smart products and data-driven services. At the same time, many incumbent firms experience a threat to their traditional value proposition and are challenged to innovate and reconfigure their existing business models. However, many of these traditional manufacturers lack or are unaware of the required capabilities for successfully reinventing their business model using IoT technologies. We therefore adopt the lens of dynamic and operational capabilities and conduct an empirical analysis of organizational capabilities required for successful IoT-enabled business model innovation (BMI). Through an exploratory, qualitative study based on interviews with decision makers in industrial manufacturing companies and experts in practice-oriented research institutions, we identify eleven distinct dynamic and operational capabilities. Our findings provide useful insights for research and practice and advance the understanding of enablers in IoT-enabled BMI

Modular Professional Services: Conceptual Goodness and Research Themes

Professional service providers are increasingly confronted with the challenge of integrating digital components and knowledge-intensive activities to standardize complex recurring tasks while remaining agile to offer customized services that fulfill diverse customer needs. Modular service design has been proposed as a mean to enable a sound balance between these contradicting aims. However, the current literature on modularity in professional services reflects inconsistencies and tensions in the concept that have hitherto hindered the development of a common point of departure for further research. This paper seeks to summarize the current theoretical discussion on the modular design of professional services and evaluates its conceptual goodness based on five established design criteria. Our findings identify weak spots in our understanding of the modularity concept in the field of professional services and highlight five prevailing research themes that build a common ground for further research to address them correspondingly from different angles

Towards an Evaluation Framework for Threat Intelligence Sharing Platforms

Threat intelligence sharing is an important countermeasure against the increasing number of security threats to which companies and governments are exposed. Its objective is the cross-organizational exchange of information about actual and potential threats. In recent years, a heterogeneous market of threat intelligence sharing platforms (TISPs) has emerged. These platforms are inter-organizational systems that support collaborative collection, aggregation, analysis and dissemination of threat-related information. Organizations that consider using TISPs are often faced with the challenge of selecting suitable platforms. To facilitate the evaluation of threat intelligence sharing platforms, we present a framework for analyzing and comparing relevant TISPs. Our framework provides a set of 25 functional and non-functional criteria that support potential users in selecting suitable platforms. We demonstrate the applicability of our evaluation framework by assessing three platforms: MISP, OTX and ThreatQ. We describe common features and differences between the three platforms