@book{Seidlmeier2004, author = {Seidlmeier, Heinrich}, title = {Process Modelling with ARISĀ®}, publisher = {Vieweg}, address = {Wiesbaden}, isbn = {3-528-05877-3}, publisher = {Technische Hochschule Rosenheim}, year = {2004}, language = {en} } @techreport{Seidlmeier2023, type = {Working Paper}, author = {Seidlmeier, Heinrich}, title = {Theory of Networks and Processes - A First Foundation of Process Networks}, series = {Rosenheim Papers in Applied Economics and Business Sciences}, journal = {Rosenheim Papers in Applied Economics and Business Sciences}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:861-opus4-22127}, pages = {9}, year = {2023}, abstract = {The impulse to think about process-induced social networks (in short: process networks) comes from the discipline of "Process Mining" (e.g. van der Aalst et al. 2005). The relevant literature refers to an "organizational view" or "organizational mining" in process mining. In essence, process mining is about creating a time-logical chain of related tasks from automatically logged user activities on a computer. In this way, real processes can be mapped and analyzed as models. As a "by-product", task-related social networks are created between the process participants through the predecessor/successor relationships in the workflow. However, it should be noted and criticized that process mining research neglects the potential of social network analysis. The extensive findings of classical network research are not taken up further. An organizational and social scientific deepening of the data-driven preliminary work is missing in this discipline. Process mining, which tends to be mathematical and technical, has not yet developed the ambition to ally itself with empirical organizational and social research. This working paper tries to counteract this. It presents a first, social science-based approach to theoretically grounding process networks.}, subject = {Business Process}, language = {en} } @techreport{Seidlmeier2024, author = {Seidlmeier, Heinrich}, title = {Process organization design by networks}, doi = {10.13140/RG.2.2.12369.13920}, pages = {24}, year = {2024}, abstract = {Organizational mining, a sub-discipline of process mining, introduced social networks based on business processes. However, process mining has only half-heartedly pursued this line of development. In particular, the well-founded results of interdisciplinary social network analysis have hardly been taken up. This article shows how the explanation and design of the phenomenon "organization" can benefit from the further development of this network view of business processes. To this end, the basic idea of social process networks is presented and the current state of research is outlined. Furthermore, social networks are presented as a new component of organization design. An interesting, far-reaching new field of research is expected. This paper presents three novel findings that could be the starting point for further research, but can also be used in practice today.}, language = {en} } @techreport{Seidlmeier2024, author = {Seidlmeier, Heinrich}, title = {Hidden networks in business processes - theoretical considerations and experimental verification}, doi = {10.13140/RG.2.2.24967.00161}, pages = {22}, year = {2024}, abstract = {The discipline of process mining was the first to demonstrate the construction of social networks from business processes. Collaboration in the process flow creates relationships between the participants. The objective of this article is to further develop this basic idea of "hidden process-induced networks" (in short: process networks) on the basis of the findings of social network research and to make a new contribution to the management and design of business processes. A contingency network theory of processes is presented for the first time as the methodological foundation for the article. In essence, it is demonstrated how the characteristics of a process network (contingency factors) can be utilized as design variables for achieving desirable process improvements. This is followed by an experimental verification and confirmation of this theory of business process design. Finally, use cases demonstrate the practical applicability of the findings. Based on experimentally obtained data, regression analyses show that there are strong correlations between certain network measures (quantitative network characteristics) and the process measures processing time and cycle time. Processes therefore not only form networks. Networks can also support the optimization of processes. Process networks can be regarded as novel, theoretically sound and empirically verified explanatory and design models for business process management.}, language = {en} }