Grisold, Thomas

Janiesch, Christian

Röglinger, Maximilian

Wynn, Moe T, Dr

English

AIS Electronic Library (AISeL)

CALL FOR PAPERSCall for Papers, Issue 5/2024Managing the Dynamics of Business ProcessesThomas Grisold • Christian Janiesch • Maximilian Röglinger • Moe Thandar WynnPublished online: 10 November 2022 The Author(s) 20221 Special IssueBusiness process management (BPM) is a holistic man-agement discipline (Rosemann and vom Brocke 2015) withan established toolbox and lifecycle of managementactivities (Dumas et al. 2018). It is a source of constantinnovation and can provide companies with competitiveadvantage. While the execution of business processes withso-called BPM systems is well-understood (Weske 2019),there is a constant influx of novel technologies and man-agement ideas that challenge and possibly re-shape the coreof BPM.In response, recent claims emphasize that the traditionalassumptions of BPM are increasingly challenged in thedigital age (Baiyere et al. 2020; Kerpedzhiev et al. 2021;Mendling et al. 2020). As new digital technologies emerge,new data streams become available and new customerneeds take shape, organizations need to grapple with everincreasing dynamics in their business environments. Thechallenge for BPM is thus tied to a tension betweenstability and change. On the one hand, organizations needto ensure that their business processes are stable and reli-able to some extent, and on the other hand, they need toconsider and react to these dynamics to remaincompetitive.There is emerging interest around the question of howorganizations can manage their business processes as theyembrace such dynamics (Grisold et al. 2022). We are,however, only beginning to understand what this means forBPM in more general terms. Hence, the aim of this specialissue is to provide space to various aspects related tomanaging the dynamics from a BPM point of view. To thisend, we are interested in a variety of perspectives thatcover technical as well as organizational and managerialaspects.On the technical side, for instance artificial intelligence(AI) rooted in machine learning algorithms (Janiesch et al.2021) has impacted BPM dynamics like any other field. AIhas been widely recognized as a driver for more granulardecision making and delegation within decision processes(Baird and Maruping 2021) as well as possibly moremachine autonomy in human-machine processes (Janieschet al. 2019). In addition, process mining based on such self-learning approaches has started to outperform traditionalprocess mining approaches (van der Aalst 2016; van derAalst and Carmona 2022) and opens the door, for example,to a more dynamic management of future events (Heinrichet al. 2021) or concept drift (Sato et al. 2022).As another example, consider how robotic processautomation (RPA) has changed the tide for many BPMendeavors. Whenever traditional BPM systems are con-sidered too heavyweight, lightweight software robots – socalled bots – mimicking human workers now provide adynamic alternative for automation (van der Aalst et al.2018) coining the term hyperautomation for rapid,T. GrisoldUniversity of Liechtenstein, Vaduz, Liechtensteine-mail: thomas.grisold@uni.liC. Janiesch (&)TU Dortmund University, Dortmund, Germanye-mail: christian.janiesch@tu-dortmund.deM. RöglingerResearch Center Finance & Information Management,Fraunhofer FIT, University of Bayreuth, Bayreuth, Germanye-mail: maximilian.roeglinger@fim-rc.deM. T. WynnQueensland University of Technology, Brisbane, Australiae-mail: m.wynn@qut.edu.au123Bus Inf Syst Eng 64(6):841–843 (2022)https://doi.org/10.1007/s12599-022-00777-5business-driven process automation anywhere. The tor-rential introduction of RPA into business practice hasrevealed many challenges not yet sufficiently understood(Syed et al. 2020), including the economics, governance,and life cycle of RPA. Further technological avenues toexplore include but are not limited to cloud computing andblockchain technology, the Internet of Things (IoT), andaugmented or virtual reality.From an organizational point of view, we are interestedin dynamics that result from inside or outside the organi-zation and affect how business processes are performed.Research in the organization sciences, for example, showshow dynamics emerge when process participants evaluatesituations and take their own decisions (Dittrich et al. 2016;Pentland et al. 2021), thus providing potential explanationsto process mining-related findings why predefined modelsare not necessarily followed (Baiyere et al. 2020; Mendlinget al. 2021). Furthermore, the growing interest in self-managed forms of organizing, such as agile or holacracy orbimodal approaches, pose new challenges and opportuni-ties for the design and management of dynamic businessprocesses (Badakhshan et al. 2019; Kremser and Xiao2021).From a managerial point of view, this also implies thatmanagers need to attend and respond to evolving dynamicsin business processes (Grisold et al. 2022). To this end,emerging digital technologies as pointed out above enableinsights into process dynamics with increasing flexibilityand detail (Leonardi and Treem 2020). However, we lack asystematic understanding and consensus of when, how, andwhy managerial practices should be informed on thegrounds of such technologies to be able to interpret andexplain unexpected dynamics (Pentland et al. 2021).2 Invited ContributionsThe ambition behind this special issue is to provide a spacefor original contributions that investigate how the dynam-ics of business processes can be represented, explained, andmanaged. Considering the strong role that emerging digitaltechnologies play in BPM, we explicitly encourage sub-missions with a socio-technical focus, merging organiza-tional, managerial, and technology-related perspectives(Sarker et al. 2019). We welcome empirical contributionsthat pursue descriptive, explanatory, or prescriptiveresearch; we also welcome conceptual work, design-ori-ented research, as well as reviews and surveys if theyprovide a unique own contribution to the discussion.Submissions should consider – but are not limited to –the following questions:Organizational and managerial aspects:• How can we manage business processes in dynamic,self-organizing environments, e.g., agile or holacracy?• What are the skills and capabilities of modern BPMmanagers who successfully leverage digitaltechnologies?• What is the impact of lightweight automation on themanagerial practices of BPM?• What kind of novel managerial tools do we need toharness hyperautomation?• What are challenges and opportunities of managingbusiness processes when the behavior of process partic-ipants is made visible through digital traces?• To what extent can theories and methods from theorganizational and managerial sciences help to explainand manage the dynamics of business processes?Technical aspects:• How can BPM technologies integrate seamlessly withemerging technologies (e.g., AI, RPA, Blockchain,IoT)?• How can AI technology enable more dynamic decisionmaking in business processes?• How does the concept of AI change the interaction anddelegation between human and machine in businessprocesses?• How do heavyweight systems (i.e., BPM) and light-weight systems (e.g., RPA) integrate harmoniously?• How can RPA be made more flexible and smarter tocope with dynamics of business processes?• How can data-driven process management be facili-tated by the next generation of BPM systems?3 Submission GuidelinesPlease submit papers by 1 Nov 2023 at the latest via thejournal’s online submission system (http://www.editorialmanager.com/buis/). Please observe the instructionsregarding the format and size of contributions to Business& Information Systems Engineering (BISE). Papers shouldadhere to the submission general BISE author guidelines(https://www.bise-journal.com/author_guidelines).All papers will be reviewed anonymously (double-blindprocess) by at least two referees regarding relevance,originality, and research quality. In addition to the editorsof the journal, including those of this special focus, dis-tinguished international scholars will be involved in thereview process.123842 T. Grisold et al.: Call for Papers, Issue 5/2024, Bus Inf Syst Eng 64(6):841–843 (2022)4 ScheduleSubmission Deadline: 01 November 2023Author Notification 1: 23 December 2023Completion Revision 1: 01 March 2024Author Notification 2: 15 April 2024Completion of Revision 2: 22 May 2024Funding Open Access funding enabled and organized by ProjektDEAL.Open Access This article is licensed under a Creative CommonsAttribution 4.0 International License, which permits use, sharing,adaptation, distribution and reproduction in any medium or format, aslong as you give appropriate credit to the original author(s) and thesource, provide a link to the Creative Commons licence, and indicateif changes were made. The images or other third party material in thisarticle are included in the article’s Creative Commons licence, unlessindicated otherwise in a credit line to the material. If material is notincluded in the article’s Creative Commons licence and your intendeduse is not permitted by statutory regulation or exceeds the permitteduse, you will need to obtain permission directly from the copyrightholder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.ReferencesBadakhshan P, Conboy K, Grisold T, vom Brocke J (2019) Agilebusiness process management: a systematic literature review andan integrated framework. Bus Proc Manag J 26(6):1505–1523Baird A, Maruping LM (2021) The next generation of research on ISuse: a theoretical framework of delegation to and from agentic ISartifacts. MIS Q 45(1):315–341Baiyere A, Salmela H, Tapanainen T (2020) Digital transformationand the new logics of business process management. Eur J InfSyst 29(3):238–259Dittrich K, Guérard S, Seidl D (2016) Talking about routines: the roleof reflective talk in routine change. Org Sci 27(3):678–697Dumas M, Rosa ML, Mendling J, Reijers HA (2018) Fundamentals ofbusiness process management, 2nd edn. Springer, HeidelbergGrisold T, Wurm B, vom Brocke J, Kremser W, Mendling J, Recker J(2022) Managing process dynamics in a digital world: integrat-ing business process management and routine dynamics in IScurricula. Commun Assoc Inf Syst 51:1–21Heinrich K, Zschech P, Janiesch C, Bonin M (2021) Process dataproperties matter: introducing gated convolutional neural net-works (GCNN) and key-value-predict attention networks (KVP)for next event prediction with deep learning. Decis Support Syst143:113494Janiesch C, Fischer M, Winkelmann A, Nentwich V (2019) Speci-fying autonomy in the internet of things: the autonomy modeland notation. Inf Syst e-Bus Manag 17(1):159–194Janiesch C, Zschech P, Heinrich K (2021) Machine learning and deeplearning. Electron Mark 31(3):685–695Kerpedzhiev GD, König UM, Röglinger M, Rosemann M (2021) Anexploration into future business process management capabilitiesin view of digitalization. Bus Inf Syst Eng 63(2):83–96Kremser W, Xiao J (2021) Self-managed forms of organizing androutine dynamics. In: Feldman MS et al (eds) Cambridgehandbook of routine dynamics. Cambridge University Press,Cambridge, pp 421–432Leonardi PM, Treem JW (2020) Behavioral visibility: a newparadigm for organization studies in the age of digitization,digitalization, and datafication. Org Stud 41(12):1601–1625Mendling J, Pentland BT, Recker J (2020) Building a complementaryagenda for business process management and digital innovation.Eur J Inf Syst 29(3):208–219Mendling J, Berente N, Seidel S, Grisold T (2021) The philosopher’scorner. ACM SIGMIS Database Database Adv Inf Syst52(2):127–140Pentland B, Vaast E, Wolf JR (2021) Theorizing process dynamicswith directed graphs: a diachronic analysis of digital trace data.MIS Q 45(2):967–984Rosemann M, vom Brocke J (2015) The six core elements of businessprocess management. Handbook on business process manage-ment, vol 1. Springer, Heidelberg, pp 105–122Sarker S, Chatterjee S, Xiao X, Elbanna A (2019) The sociotechnicalaxis of cohesion for the IS discipline: its historical legacy and itscontinued relevance. MIS Q 43(3):695–719Sato DMV, De Freitas SC, Barddal JP, Scalabrin EE (2022) A surveyon concept drift in process mining. ACM Comput Surv54(9):1–38Syed R, Suriadi S, Adams M, Bandara W, Leemans SJJ, Ouyang C,ter Hofstede AHM, van de Weerd I, Wynn MT, Reijers HA(2020) Robotic process automation: contemporary themes andchallenges. Comput Ind 115:103162van der Aalst WMP (2016) Process mining: data science in action,2nd edn. Springer, Heidelbergvan der Aalst WMP, Carmona J (eds) (2022) Process mininghandbook. Springer, Chamvan der Aalst WMP, Bichler M, Heinzl A (2018) Robotic processautomation. Bus Inf Syst Eng 60(4):269–272Weske M (2019) Business process management: concepts, languages,architectures, 3rd edn. Springer, Heidelberg123T. Grisold et al.: Call for Papers, Issue 5/2024, Bus Inf Syst Eng 64(6):841–843 (2022) 843

Call for Papers, Issue 5/2024

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Call for Papers, Issue 5/2024

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