Detecting temporal workarounds in business processes – A deep-learning-based method for analysing event log data - Weinzierl, Sven; Wolf, Verena; Pauli, Tobias; Beverungen, Daniel; Matzner, Martin (Journal of Business Analytics, 2022)
Business process management distinguishes the actual “as-is” way work is accomplished and a prescribed or desired “to-be” version of a process. In practice, many different causes trigger a process’s drifting away from a once designed to-be state. For instance, employees may “workaround” the proposed systems or protocols in an attempt to increase their effectiveness or efficiency in day-to-day work. Workarounds are often viewed as negative deviations that interfere with security and quality requirements. This article emphasises their role in identifying and restructuring dysfunctional or obsolete processes. So far, ethnography or critical incident techniques are used to identify how and why workarounds emerge. We design a method that helps detect different types of workarounds in event logs using a deep-learning-based approach. Event logs are large data sets documenting the completion of process work based on information systems. Our method tracks indications of potential workarounds in the early stages of their emergence among deviating behaviour. Our evaluation based on four real-life event logs reveals that our method performs well and works best for business processes with fewer variations and a higher number of different activities. The proposed method is one of the first information technology artefacts to bridge the boundaries between the complementing research disciplines of organisational routines and business processes managemen
Keywords: Workaround; Business Process; Deep Learning; Process Mining; Routines

Detecting workarounds in business processes — A deep learning method for analyzing event logs - Weinzierl, Sven; Wolf, Verena; Pauli, Tobias; Beverungen, Daniel; Matzner, Martin (Proceedings of the 28th European Conference on Information Systems, 2020)
Business processes performed in organizations often deviate from the abstract process models issued by designers. Workarounds that are carried out by process participants to increase the effectiveness or efficiency of their tasks are often viewed as negative deviations from prescribed business processes, interfering with their efficiency and quality requirements. But workarounds might also play an important role in identifying and re-structuring inefficient, dysfunctional, or obsolete processes. While ethnography or critical incident techniques can serve to identify how and why workarounds emerge, we need automated methods to detect workarounds in large data sets. We set out to design a method that implements a deep-learning-based approach for detecting workarounds in event logs. An evaluation with three public real-life event logs exhibits that the method can identify workarounds best in standardized business processes that contain fewer variations and a higher number of different activities. Our method is one of the first IT artifacts to bridge boundaries between the complementing research disciplines of organizational routines and business processes management.<br
Keywords: Workarounds; Business Processes; Deep Learning; Process Mining

Digital Industrial Platforms - Pauli, Tobias; Fielt, Erwin; Matzner, Martin (Business & Information Systems Engineering, 2021)

Digitization-enabled Innovation in Service Systems: An Empirical Analysis of the German MDAX Companies - Genennig, Stefan; Pauli, Tobias; Roth, Angela; Möslein, Kathrin (European Academy of Management (EURAM), 2018)

Driving Generativity in Industrial IoT Platform Ecosystems - Marheine, Christian; Pauli, Tobias (Proceedings of the 41st International Conference on Information Systems, 2020)
While the generativity of digital platform ecosystems has been studied extensively in many business-to-consumer domains, research on the novel phenomenon of IIoT platforms is sparse. The peculiarities of IIoT platform ecosystems are a double-edged sword: On the one hand, the heterogeneity of actors and devices leads to high generative potential. On the other hand, the resulting complexity can impede its realization. Even though generativity is often seen as a platform’s inherent characteristic, our study suggests that it must be driven deliberately in complex domains like the IIoT. As initial results of a theory elaboration case study, we propose two modes that drive generativity in the form of a virtuous cycle by moving from abstraction of individual solutions to concretization of generic modules and vice versa. Our final results will contribute to extant literature on generativity in complex digital platform ecosystems and provide valuable insights for practitioners in the IIoT domai

From Services to Smart Services: Can Service Engineering Methods get Smarter as well? - Marx, Emanuel; Pauli, Tobias; Fielt, Erwin; Matzner, Martin (Proceedings of the 15th International Conference on Wirtschaftsinformatik (WI), 2020)
Progress in technologies such as cloud computing or artificial intelligence currently paves the way for services that rely on the exploitation of data. The resulting smart services, however, are only gradually finding their way into practical application. A reason for this delay has been identified in the limited applicability of existing service engineering methods for smart services. In this paper, we identify critical perspectives to address in smart service engineering. Subsequently, we conduct a literature review to identify the extent to which these perspectives are covered by current smart service engineering methods. Our results indicate that even though there is a significant number of smart service engineering methods, some perspectives are rarely considered. We offer practitioners and researchers an overview of the status quo of smart service engineering, thus supporting the former in the selection of methods and pointing out avenues for future research to the latte
Keywords: smart service; service innovation; smart service engineering; service development; systematic literature review

From Suppliers to Complementors: Motivational Factors for Joining Industrial Internet of Things Platform Ecosystems - Marheine, Christian; Pauli, Tobias; Marx, Emanuel; Back, Andrea; Matzner, Martin (Proceedings of the 54th Hawaii International Conference on System Sciences (HICSS), 2021)
Spurred by the internet of things, industry firms are increasingly establishing platforms that animate an ecosystem of external actors to provide complementary offerings. But why do independent firms decide to join these ecosystems and to become complementors? The goal of this study is to disentangle their motivational factors in the context of the industrial internet of things. A theoretical framework is developed a priori based on the knowledge-based view of the firm and complementary logics. The framework is empirically explored using a case study design. Our results indicate that financial, technology, and knowledge gains positively influence the decision of complementors to join the ecosystem. Yet, our interviews reveal relative differences in motivations based on complementors’ uncertainty. Our findings contribute to the research on joining nascent digital platform ecosystems from a complementor perspective and the growing stream of research on industrial internet of things platform
Keywords: Industrial Internet of Things; Platform; Ecosystem

Inhibitors and Enablers of Leverage in Digital Industrial Platform Ecosystems - Pauli, Tobias; Marx, Emanuel; Fielt, Erwin; Marheine, Christian; Matzner, Martin (Business & Information Systems Engineering, 2025)
Digital platforms have demonstrated their disruptive power across various domains, and an increasing number of manufacturing firms have embarked on establishing digital industrial platforms for emerging technologies like the Industrial Internet of Things. Given the technical and organizational complexity of digital industrial platforms, the ways in which complementors can create value by interacting and engaging with them may differ for these platforms. Drawing on a case study conducted at a large multinational platform provider, the article explores how complementors can use digital industrial platforms to their advantage. To this end, the study adopts the concept of leverage, which refers to the ability of platform ecosystems to exert a significant degree of impact that is disproportionate to the input required. The findings indicate that complementors currently primarily benefit from production leverage, utilizing the platform as a technological foundation for individual solutions. However, the utilization of the platform as a marketplace for innovative and generically distributable applications that benefit from innovation and transaction leverage is limited. This is due to a variety of inhibitors, which the platform owner tries to mitigate via enablers through deliberate governance in the form of boundary resources. By unveiling domain-specific manifestations, inhibitors, and enablers across different types of leverage, the study contextualizes leverage within the domain of digital industrial platforms and stresses the need for adopting platform and ecosystem thinking and providing relational governance mechanisms. In addition, it extends the notion of architectural leverage by emphasizing the leveraging ecosystem and its governance through the deliberate orchestration of complementor engagement and underscoring ecosystem leverage based on value co-creation and coordination.
CRIS-Team Scopus Importer:2025-03-07
Keywords: Complementor; Digital industrial platform; Digital platform; Leverage; Manufacturing; Platform ecosystem

Leveraging Industrial IoT Platform Ecosystems: Insights from the Complementors' Perspective - Pauli, Tobias; Marx, Emanuel; Matzner, Martin (Proceedings of the 28th European Conference on Information Systems (ECIS), 2020)
To create value from the increasing amount of data produced by the Industrial Internet of Things (IIoT), many firms establish platforms to collect data and make it available to third parties. Thus, IIoT platforms rely on a diverse ecosystem of complementors for value creation. While platform ecosystems have received considerable attention in research, most studies focus on the platform owner and domains such as video game or mobile platforms. In this article, we conducted a case study to shed light on why complementors choose specific IIoT platforms and how they leverage IIoT platform ecosystems for their benefit. To this end, we collected interview data from 15 firms that provide complementary offerings to an IIoT platform. We identified platform owner relationship, platform owner background, customer decision, platform market position, and platform features as vital criteria for platform choice. Additionally, our findings show that complementors leverage IIoT platforms primarily as a technological basis for individual solutions but not as a marketplace for generic applications. Our study extends research on platform ecosystems by illuminating the complementors’ perspective and adding insights from the IIoT domain. Additionally, our findings provide guidance for platform owners on how to design IIoT platform business models and facilitate leverag
Keywords: Industrial Internet of Things; Platform; Ecosystem; Complementor; Leverage

Modeling Platform Ecosystems - Pauli, Tobias; Marx, Emanuel; Dunzer, Sebastian; Matzner, Martin (ER Forum, Demo and Posters co-located with 39th International Conference on Conceptual Modeling (ER), 2020)
Platforms facilitate the creation of complementary modulesby third parties and act as intermediaries between different groups of ac-tors. Due to the high degree of collaboration between actors, ecosystemsevolve around such platforms. As a result of digitalization, platform busi-ness models are becoming viable in more and more domains. Despite theincreasing variety of different platform ecosystems, means to clearly spec-ify them are scarce. This conceptual ambiguity impedes comparabilityof research and knowledge accumulation. To solve this problem, we pro-pose a domain-specific platform ecosystems modeling language (PEML)which builds on seminal platform ecosystem literature. We demonstratePEML by modeling two real-life platform ecosystems based on onlinecase studies. Our results support researchers and practitioners alike inclearly specifying platform ecosystem
Keywords: Platform·Ecosystem·Domain-Specific Modeling Language

Pins on the Map: Navigating the Ambiguous Landscape of Generativity in Digital Platform Ecosystems - Pauli, Tobias (The Role of e-Business During the Time of Grand Challenges, 2021)
Generativity is the main influencing mechanism for platform ecosystem evolution. As the literature on generativity grows, however, researchers have criticized that the concept itself remains rather fuzzy and ambiguous. Thus, the paper at hand aspires to make generativity more tangible. Based on a literature review, we uncover what is known about the nature, measurement, and management of generativity. Our results show that generativity is indeed still a somewhat elusive concept. While generativity is critical for the success of platform ecosystems, it also has negative effects. While there are valid approaches to measure generativity ex-post, leading indicators are still scarce. Lastly, while there are ways to manage generativity, the majority of the literature stresses its chaotic and serendipitous nature. By mapping the ambiguous landscape of generativity, we provide researchers and practitioners with a clearer understanding, further paving the way for generativity to become a valuable concept for understanding platform ecosystem evolutio
Keywords: digital platform; platform ecosystem; generativity; innovation

Pins on the Map: Navigating the Ambiguous Landscape of Generativity in Digital Platform Ecosystems - Pauli, Tobias (Lecture Notes in Business Information Processing, 2021)
Generativity is the main influencing mechanism for platform ecosystem evolution. As the literature on generativity grows, however, researchers have criticized that the concept itself remains rather fuzzy and ambiguous. Thus, the paper at hand aspires to make generativity more tangible. Based on a literature review, we uncover what is known about the nature, measurement, and management of generativity. Our results show that generativity is indeed still a somewhat elusive concept. While generativity is critical for the success of platform ecosystems, it also has negative effects. While there are valid approaches to measure generativity ex-post, leading indicators are still scarce. Lastly, while there are ways to manage generativity, the majority of the literature stresses its chaotic and serendipitous nature. By mapping the ambiguous landscape of generativity, we provide researchers and practitioners with a clearer understanding, further paving the way for generativity to become a valuable concept for understanding platform ecosystem evolution.
CRIS-Team Scopus Importer:2021-08-20
Keywords: Digital platform; Generativity; Innovation; Platform ecosystem

The Generativity of Industrial IoT Platforms: Beyond Predictive Maintenance? - Pauli, Tobias; Lin, Yanpei (Proceedings of the 40th International Conference on Information Systems, 2019)
As the Industrial Internet of Things (IIoT) increasingly connects various assets, firms are establishing platforms to harness the data and make it available to third parties to create complementary offerings. As a result, IIoT platforms possess high generativity, i.e. the potential of triggering a variety of innovations. However, little is known to date about how this generative potential is leveraged. Therefore, in this study, we analyzed the solutions provided via the IIoT platform of a large European industrial firm along two dimensions: the diversity of solution scenarios they address, and the diversity of capabilities they display. Our preliminary results indicate that the diversity of scenarios addressed by IIoT solutions is quite high, whereas the diversity of capabilities is mainly limited to monitoring. Our study provides empirical insights on the generativity of IIoT platforms and extends the literature on digital platforms by indicating that generativity might require a more differentiated analysis.<br
Keywords: IIoT Platform; Digital Platform; Generativity; Industrial Internet of Things

Transitioning to Platform-based Services and Business Models in a B2B Environment - Matzner, Martin; Pauli, Tobias; Marx, Emanuel; Anke, Jürgen; Poeppelbuss, Jens; Fielt, Erwin; Gregor, Shirley; Sun, Ruonan; Hydle, Katja Maria; Aas, Tor Helge; Aanestad, Margunn; Gordijn, Jaap; et al. (Journal of Service Management Research, 2021)
Given the considerable success of companies such as Apple, Amazon or Airbnb, the term platform is on everyone’s lips today. Accordingly, platforms have long since also found their way into service science. However, mastering the transition from established product-sales-based offerings to platform-based services and business models comes with a multitude of challenges. In a B2B context, incumbent companies need to carefully evaluate how they can benefit from the establishment of platforms, especially in light of the effects on their existing business models and ties to other actors. Hence, we invited scholars with different backgrounds to provide viewpoints on the opportunities and challenges of the transition to platform-based services and business models in a B2B environment. The individual commentaries provide various insights on how to conduct this transition and benefit from it successfully. To do so, they contrast different approaches for establishing and governing ecosystems around platforms, discuss B2B-specific pitfalls and opportunities of platform business models, uncover the supporting role of platforms for smart service development, and stress the importance of platform and ecosystem thinking as a necessary mindse
Keywords: Digital platforms; Business models; Ecosystems; Smart services; Business-to-Business