@inproceedings{HafnerThim2021, author = {Hafner, Julee and Thim, Christof}, title = {Knowledge, innovation and entrepreneurial systems track innovation in organizations}, series = {Proceedings of the 54th Hawaii International Conference on System Sciences}, booktitle = {Proceedings of the 54th Hawaii International Conference on System Sciences}, editor = {Bui, Tung}, publisher = {University of Hawai'i at Manoa, Hamilton Library}, address = {Honolulu, HI}, isbn = {978-0-9981331-4-0}, pages = {5046 -- 5047}, year = {2021}, abstract = {We welcome you to the 54th Hawaii International Conference on System Sciences (HICSS-54) conference. This is the fifth year for the Organizational Learning Minitrack which has had the usual growing pains: two years ago, we added the topic of Unlearning and joined with the Intentional Forgetting Minitrack - as these topics are all organizationally-based knowledge management issues. We proudly bring you the latest research focused on the methods to develop and maintain organizational learning within the Knowledge Innovation and Entrepreneurial Systems Track. The ability to update, change and use current knowledge effectively, especially in light of the ongoing knowledge explosion, can be costly for any organization. Organizations that consider themselves "learning" or "knowledge-based" organizations must develop a competent workforce using KM strategies. Success in organizations involves developing a variety of human factors for changing competencies. With technological change, modification and revisions, many skills require updating for a competitive advantage in the marketplace. The focus on new techniques and insights into how individuals and organizations use their knowledge is our focus for the improvement of organizational learning in this Minitrack.}, language = {en} } @inproceedings{HafnerThim2022, author = {Hafner, Julee and Thim, Christof}, title = {Innovation in organizations: learning, unlearning, and intentional forgetting}, series = {Proceedings of the 55th Hawaii International Conference on System Sciences (HICSS)}, booktitle = {Proceedings of the 55th Hawaii International Conference on System Sciences (HICSS)}, publisher = {University of Hawai'i at Manoa Hamilton Library}, address = {Honolulu, HI}, isbn = {978-099813315-7}, pages = {4784 -- 4785}, year = {2022}, abstract = {We welcome you to the 53rd Hawaii International Conference on System Sciences (HICSS) conference. After joining with Intentional Forgetting Minitrack last year, this is the fourth year of the Organizational Learning Minitrack. We add Unlearning, and Intentional Forgetting to proudly bring you the latest research focused on organizational learning issues within the Knowledge Innovation and Entrepreneurial Systems Track. The ability to update, change and use current knowledge effectively, especially in light of the ongoing knowledge explosion, can be costly for any organization. Organizations that consider themselves "learning" or "knowledge-based" organizations must develop a competent workforce using KM strategies. Success in organizations involves developing a variety of human factors for changing competencies. With technological change, modification and revisions, many skills require updating for a competitive advantage in the marketplace. The focus on new techniques and insights into how individuals and organizations use their knowledge is our focus for the improvement of organizational learning in this Minitrack.}, language = {en} } @incollection{BenderThim2021, author = {Bender, Benedict and Thim, Christof}, title = {Entering complementary markets on software platforms}, series = {Platform coring on digital software platforms}, booktitle = {Platform coring on digital software platforms}, editor = {Bender, Benedict}, publisher = {Springer Gabler}, address = {Wiesbaden}, isbn = {978-3-658-34798-7}, doi = {10.1007/978-3-658-34799-4_7}, pages = {149 -- 199}, year = {2021}, abstract = {Software platforms regularly introduce new features to remain competitive. While platform innovation is considered to be a critical success factor, adding certain features could hurt the ecosystem. If platform owners provide functionality that was previously provided by a contributor, the owners enter complementary product spaces. Complementary market entry frequently occurs on software platforms and is a major concern for third-party developers. Divergent findings on the impact of complementary market entry call for the consideration of additional factors. As prior research neglected the third-party perspective, this contribution aims to address this gap. We explore the use of measures to prevent complementary market entry using a survey approach on browser platforms. The research model is tested with 655 responses among developer from Mozilla Firefox and Google Chrome. To explain countermeasures employment, developer's attitude and perceived likelihood are important. The results reveal that developers employ countermeasures if complementary market entry is assessed negatively and perceived as likely for their extension. Differences among browser platforms concerning complementary market entry are identified. Product spaces of extensions being available on multiple platforms are less likely to be entered and more heavily protected. Implications for research and stakeholders, i.e. platform owners and contributors are discussed.}, language = {en} } @incollection{BenderThimLinke2021, author = {Bender, Benedict and Thim, Christof and Linke, Felix}, title = {Platform coring in the browser domain}, series = {Platform coring on digital software platforms}, booktitle = {Platform coring on digital software platforms}, editor = {Bender, Benedict}, publisher = {Springer Gabler}, address = {Wiesbaden}, isbn = {978-3-658-34798-7}, doi = {10.1007/978-3-658-34799-4_6}, pages = {119 -- 148}, year = {2021}, abstract = {Modern browsers are digital software platforms, as they allow third parties to extend functionality by providing extensions. In a highly competitive environment, differentiation through provided functionality is a key factor for browser platforms. As the development of browsers progress, new functions are constantly being released. Browsers could thus enter complementary markets by adding functionality previously provided by third-party extensions, which is referred to as 'platform coring'. Previous studies have missed the perspective of the parties involved. To address this gap, we conducted interviews with third-party and core developers in the security and privacy domain from Firefox and Chrome. This study provides three contributions. First, insights into stakeholder-specific issues concerning coring. Second, measures to prevent coring. Third, strategical guidance for developers and owners. Third-party vendors experienced and core developers confirmed that coring occurs on browser platforms. While developers with extrinsic motivations assess coring negatively, developers with intrinsic motivations perceive coring positively.}, language = {en} } @incollection{ThimGrumSchueffleretal.2021, author = {Thim, Christof and Grum, Marcus and Sch{\"u}ffler, Arnulf and Roling, Wiebke and Kluge, Annette and Gronau, Norbert}, title = {A concept for a distributed Interchangeable knowledge base in CPPS}, series = {Towards sustainable customization: cridging smart products and manufacturing systems}, booktitle = {Towards sustainable customization: cridging smart products and manufacturing systems}, editor = {Andersen, Ann-Louise and Andersen, Rasmus and Brunoe, Thomas Ditlev and Larsen, Maria Stoettrup Schioenning and Nielsen, Kjeld and Napoleone, Alessia and Kjeldgaard, Stefan}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-90699-3}, doi = {10.1007/978-3-030-90700-6_35}, pages = {314 -- 321}, year = {2021}, abstract = {As AI technology is increasingly used in production systems, different approaches have emerged from highly decentralized small-scale AI at the edge level to centralized, cloud-based services used for higher-order optimizations. Each direction has disadvantages ranging from the lack of computational power at the edge level to the reliance on stable network connections with the centralized approach. Thus, a hybrid approach with centralized and decentralized components that possess specific abilities and interact is preferred. However, the distribution of AI capabilities leads to problems in self-adapting learning systems, as knowledgebases can diverge when no central coordination is present. Edge components will specialize in distinctive patterns (overlearn), which hampers their adaptability for different cases. Therefore, this paper aims to present a concept for a distributed interchangeable knowledge base in CPPS. The approach is based on various AI components and concepts for each participating node. A service-oriented infrastructure allows a decentralized, loosely coupled architecture of the CPPS. By exchanging knowledge bases between nodes, the overall system should become more adaptive, as each node can "forget" their present specialization.}, language = {en} } @incollection{GrumThimGronau2021, author = {Grum, Marcus and Thim, Christof and Gronau, Norbert}, title = {Aiming for knowledge-transfer-optimizing intelligent cyber-physical systems}, series = {Towards sustainable customization : cridging smart products and manufacturing systems}, booktitle = {Towards sustainable customization : cridging smart products and manufacturing systems}, editor = {Andersen, Ann-Louise and Andersen, Rasmus and Brunoe, Thomas Ditlev and Larsen, Maria Stoettrup Schioenning and Nielsen, Kjeld and Napoleone, Alessia and Kjeldgaard, Stefan}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-90699-3}, doi = {10.1007/978-3-030-90700-6_16}, pages = {149 -- 157}, year = {2021}, abstract = {Since more and more production tasks are enabled by Industry 4.0 techniques, the number of knowledge-intensive production tasks increases as trivial tasks can be automated and only non-trivial tasks demand human-machine interactions. With this, challenges regarding the competence of production workers, the complexity of tasks and stickiness of required knowledge occur [1]. Furthermore, workers experience time pressure which can lead to a decrease in output quality. Cyber-Physical Systems (CPS) have the potential to assist workers in knowledge-intensive work grounded on quantitative insights about knowledge transfer activities [2]. By providing contextual and situational awareness as well as complex classification and selection algorithms, CPS are able to ease knowledge transfer in a way that production time and quality is improved significantly. CPS have only been used for direct production and process optimization, knowledge transfers have only been regarded in assistance systems with little contextual awareness. Embedding production and knowledge transfer optimization thus show potential for further improvements. This contribution outlines the requirements and a framework to design these systems. It accounts for the relevant factors.}, language = {en} } @incollection{ThimGronauHaaseetal.2023, author = {Thim, Christof and Gronau, Norbert and Haase, Jennifer and Grum, Marcus and Sch{\"u}ffler, Arnulf and Roling, Wiebke and Kluge, Annette}, title = {Modeling change in business processes}, series = {Business modeling and software design}, booktitle = {Business modeling and software design}, editor = {Shishkov, Boris}, publisher = {Springer Nature}, address = {Cham}, isbn = {978-3-031-36756-4}, doi = {10.1007/978-3-031-36757-1_1}, pages = {3 -- 17}, year = {2023}, abstract = {Business processes are regularly modified either to capture requirements from the organization's environment or due to internal optimization and restructuring. Implementing the changes into the individual work routines is aided by change management tools. These tools aim at the acceptance of the process by and empowerment of the process executor. They cover a wide range of general factors and seldom accurately address the changes in task execution and sequence. Furthermore, change is only framed as a learning activity, while most obstacles to change arise from the inability to unlearn or forget behavioural patterns one is acquainted with. Therefore, this paper aims to develop and demonstrate a notation to capture changes in business processes and identify elements that are likely to present obstacles during change. It connects existing research from changes in work routines and psychological insights from unlearning and intentional forgetting to the BPM domain. The results contribute to more transparency in business process models regarding knowledge changes. They provide better means to understand the dynamics and barriers of change processes.}, language = {en} } @inproceedings{GrumThimRolingetal.2023, author = {Grum, Marcus and Thim, Christof and Roling, Wiebke and Sch{\"u}ffler, Arnulf and Kluge, Annette and Gronau, Norbert}, title = {AI case-based reasoning for artificial neural networks}, series = {Artificial intelligence and industrial applications}, volume = {771}, booktitle = {Artificial intelligence and industrial applications}, editor = {Masrour, Tawfik and El Hassani, Ibtissam and Barka, Noureddine}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-43523-2}, doi = {10.1007/978-3-031-43524-9_2}, pages = {17 -- 35}, year = {2023}, abstract = {Faced with the triad of time-cost-quality, the realization of production tasks under economic conditions is not trivial. Since the number of Artificial-Intelligence-(AI)-based applications in business processes is increasing more and more nowadays, the efficient design of AI cases for production processes as well as their target-oriented improvement is essential, so that production outcomes satisfy high quality criteria and economic requirements. Both challenge production management and data scientists, aiming to assign ideal manifestations of artificial neural networks (ANNs) to a certain task. Faced with new attempts of ANN-based production process improvements [8], this paper continues research about the optimal creation, provision and utilization of ANNs. Moreover, it presents a mechanism for AI case-based reasoning for ANNs. Experiments clarify continuously improving ANN knowledge bases by this mechanism empirically. Its proof-of-concept is demonstrated by the example of four production simulation scenarios, which cover the most relevant use cases and will be the basis for examining AI cases on a quantitative level.}, language = {en} }