Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-848d4c4894-mwx4w Total loading time: 0 Render date: 2024-06-16T16:15:04.343Z Has data issue: false hasContentIssue false

Chapter 37 - Business Process Management and Routine Dynamics

from Part IV - Related Communities of Thought

Published online by Cambridge University Press:  11 December 2021

By
Bastian Wurm ,
Thomas Grisold ,
Jan Mendling  and
Jan vom Brocke
Edited by
Martha S. Feldman ,
Brian T. Pentland ,
Luciana D'Adderio ,
Katharina Dittrich ,
Claus Rerup  and
David Seidl
Martha S. Feldman
Affiliation:
University of California, Irvine
Brian T. Pentland
Affiliation:
Michigan State University
Luciana D'Adderio
Affiliation:
University of Edinburgh
Katharina Dittrich
Affiliation:
University of Warwick
Claus Rerup
Affiliation:
Frankfurt School of Finance and Management
David Seidl
Affiliation:
University of Zurich
Get access

Summary

Routine dynamics and Business Process Management (BPM) are two academic disciplines that investigate sequences of action for carrying out work in organizations. Even though they share this phenomenon of interest, there are fundamental differences that separate both research areas. In this chapter, we take a first step to overcome this divide. To do this, we portray BPM by use of the business process lifecycle. The lifecycle well adopted instrument that allows us to describe how activities in BPM are interlinked and discuss the state of the art. Based on these insights, we develop multiple directions how routine dynamics and BPM can learn from and contribute to one another. We believe that a closer integration of both research areas can help to advance how we study and theorize about processes in organizations.

Keywords

Routinesroutine dynamicsbusiness process managementbusiness processprocess mining
Type
Chapter
Information
Cambridge Handbook of Routine Dynamics , pp. 513 - 524
Publisher: Cambridge University Press
Print publication year: 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alter, S. (2014). Theory of workarounds. Communications of the Association for Information Systems, 34, 1041–1066.Google Scholar
Altinkemer, K., Ozcelik, Y. and Ozdemir, Z. D. (2011). Productivity and performance effects of business process reengineering: A firm-level analysis. Journal of Management Information Systems, 27(4), 129–162.CrossRefGoogle Scholar
Becker, M. C. (2004). Organizational routines: A review of the literature. Industrial and Corporate Change, 13(4), 643–677.CrossRefGoogle Scholar
Berente, N., Lyytinen, K., Yoo, Y. and King, J. L. (2016). Routines as shock absorbers during organizational transformation: Integration, control, and NASA’ s Enterprise Information System. Organization Science, 27(3), 551–572.CrossRefGoogle Scholar
Berente, N., Seidel, S. and Safadi, H. (2019). Data-driven computationally-intensive theory development. Information Systems Research, 30(1), iii–viii.Google Scholar
Beverungen, D. (2014). Exploring the interplay of the design and emergence of business processes as organizational routines. Business & Information Systems Engineering, 6(4), 191–202.CrossRefGoogle Scholar
Birnholtz, J. P., Cohen, M. D. and Hoch, S. V. (2007). Organizational character: On the regeneration of Camp Poplar Grove. Organization Science, 18(2), 315–332.Google Scholar
Bose, R. P. J. C., van Der Aalst, W. M. P., Žliobaite, I. and Pechenizkiy, M. (2011). Handling concept drift in process mining. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6741 LNCS, 391–405.Google Scholar
Bucher, S. and Langley, A. (2016). The interplay of reflective and experimental spaces in interrupting and reorienting Routine Dynamics. Organization Science, 27(3), 594–613.Google Scholar
D’Adderio, L. (2011). Artifacts at the centre of routines: Performing the material turn in routines theory. Journal of Institutional Economics, 7(2), 197–230.CrossRefGoogle Scholar
Dittrich, K., Guérard, S. and Seidl, D. (2016). Talking about routines: The role of reflective talk in routine change. Organization Science, 27(3), 678–697.CrossRefGoogle Scholar
Dittrich, K. and Seidl, D. (2018). Emerging intentionality in routine dynamics: A pragmatist view. Academy of Management Journal, 61(1), 111–138.CrossRefGoogle Scholar
Dumas, M., La Rosa, M., Mendling, J. and Reijers, H. A. (2018). Fundamentals of Business Process Management, 2nd ed. Heidelberg: Springer.Google Scholar
Feldman, M. S. and Pentland, B. T. (2003). Reconceptualizing organizational routines as a source of flexibility and change. Administrative Science Quarterly, 48(1), 94–118.Google Scholar
Feldman, M. S., Pentland, B. T., D’Adderio, L. and Lazaric, N. (2016). Beyond routines as things: Introduction to the special issue on Routine Dynamics. Organization Science, 27(3), 505–513.Google Scholar
Figl, K., Mendling, J. and Strembeck, M. (2013). The influence of notational deficiencies on process model comprehension. Journal of the Association of Information Systems, 14(6), 312–338.Google Scholar
Gaskin, J., Berente, N., Lyytinen, K. and Yoo, Y. (2014). Toward generalizable sociomaterial inquiry: A computational approach for zooming in and out of sociomaterial routines. Management Information Systems Quarterly, 38(3), 849–871.CrossRefGoogle Scholar
Goh, K. T. and Pentland, B.T. (2019). From actions to paths to patterning: Toward a dynamic theory of patterning in routines. Academy of Management Journal, 62(6), 1901–1929.CrossRefGoogle Scholar
Gonzalez-Lopez, F. and Bustos, G. (2019). Business process architecture design methodologies: A literature review. Business Process Management Journal, 25(6), 1317–1334.Google Scholar
Grisold, T., Wurm, B., Mendling, J. and vom Brocke, J. (2020). Using process mining to support theorizing about change in organizations. In 53rd Hawaiian International Conference on System Sciences (HICSS 2020).Google Scholar
Grover, V., Teng, J., Segars, A. H. and Fiedler, K. (1998). The influence of information technology diffusion and business process change on perceived productivity: The IS executive’s perspective. Information & Management, 34(3), 141–159.CrossRefGoogle Scholar
Habermas, J. (1984). The Theory of Communicative Action. Boston: Beacon Press.Google Scholar
Hammer, M. and Champy, J. (1993). Reengineering the Corporation: A Manifesto for Business Revolution. New York: HarperCollins.Google Scholar
Hompes, B. F. A., Buijs, J., van der Aalst, W. M. P., Dixit, P. M. and Buurman, J. (2015). Discovering Deviating cases and process variants using trace clustering. In 27th Benelux Conference on Artificial Intelligence (BNAIC).Google Scholar
Howard-Grenville, J. and Rerup, C. (2017). A process perspective on organizational routines. In Langley, A. and Tsoukas, H., eds., The Sage Handbook of Process Organization Studies. Los Angeles, London, New Delhi, Singapore,Washington DC, Melbourne: Sage, pp. 323–339.Google Scholar
Kettinger, W. J., Teng, J. T. C. and Guha, S. (1997). Business process change: A study of methodologies, techniques, and tools. MIS Quartely, 21(1), 55–80.Google Scholar
Kremser, W. and Schreyögg, G. (2016). The dynamics of interrelated routines: Introducing the cluster level. Organization Science, 27, 698–721.CrossRefGoogle Scholar
Kuhn, T. (1970). The Structure of Scientific Revolutions, 2nd ed. Chicago: University of Chicago Press.Google Scholar
Kummer, T. F., Recker, J. and Mendling, J. (2016). Enhancing understandability of process models through cultural-dependent color adjustments. Decision Support Systems, 87, 1–12.CrossRefGoogle Scholar
Laguna, M. and Marklund, J. (2013). Business Process Modeling, Simulation and Design. Boca Raton, FL: CRC Press.Google Scholar
Leonardi, P. M. (2011). When flexible routines meet flexible technologies: Affordance, constraint, and the imbrication of human and material agencies. MIS Quarterly, 35(1), 147–167.CrossRefGoogle Scholar
Lindberg, A., Berente, N., Gaskin, J. and Lyytinen, K. (2016). Coordinating interdependencies in online communities: A study of an open source software project. Information Systems Research, 27(4), 751–772.Google Scholar
Mendling, J. (2016). From scientific process management to process science: Towards an empirical research agenda for Business Process Management. In Hochreiner, C. and Schulte, S., (eds.), 8th ZEUS Workshop (ZEUS 2016).Google Scholar
Mendling, J., Berente, N., Seidel, S. and Grisold, T. (2021). Pluralism and pragmatism in the information systems field: The case of research on business processes and organizational routines. The Data Base for Advances in Information Systems, 52(2), 127–140.Google Scholar
Miller, K. D., Pentland, B. T. and Choi, S. (2012). Dynamics of performing and remembering organizational routines. Journal of Management Studies, 49(8), 1536–1558.CrossRefGoogle Scholar
Orlikowski, W. J. and Scott, S. V (2008). Sociomateriality: Challenging the separation of technology, work and organizing. The Academy of Management Annals, 2(1), 433–474.Google Scholar
Pentland, B. T. and Feldman, M. S. (2005). Organizational routines as a unit of analysis. Industrial and Corporate Change, 14(5), 793–815.Google Scholar
Pentland, B. T. and Feldman, M. S. (2008). Designing routines: On the folly of designing artifacts, while hoping for patterns of action. Information and Organization, 18(4), 235–250.CrossRefGoogle Scholar
Pentland, B. T. and Rueter, H. H. (1994). Organizational routines as grammars of action. Administrative Science Quarterly, 39(3), 484–510.CrossRefGoogle Scholar
Pentland, B. T., Vaast, E. and Wolf, R. (2021). Theorizing process dynamics with directed graphs: A diachronic analysis of digital trace data. MIS Quartely, 45(2), 967–984.Google Scholar
Polyvyanyy, A., Solti, A., Weidlich, M., Di Ciccio, C. and Mendling, J. (2018). Behavioural quotients for precision and recall in process mining. Technical Report, (March), 1–19.Google Scholar
Recker, J. (2014). Suggestions for the next wave of BPM research: Strengthening the theoretical core and exploring the protective belt. Journal of Information Technology Theory and Application, 15(2), 5–20.Google Scholar
Recker, J. (2015). Evidence-based Business Process Management: Using digital opportunities to drive organizational innovation. In vom Brocke, J. and Schmiedel, T., eds., BPM-Driving Innovation in a Digital World. Cham: Springer, pp. 129–143.CrossRefGoogle Scholar
Recker, J. and Mendling, J. (2016). The state of the art of Business Process Management research as published in the BPM Conference: Recommendations for progressing the field. Business & Information Systems Engineering, 58(1), 55–72.CrossRefGoogle Scholar
Reijers, H. A. and Mansar, L. S. (2005). Best practices in business process redesign: An overview and qualitative evaluation of successful redesign heuristics. Omega, 33(4), 283–306.Google Scholar
Rosemann, M. and vom Brocke, J. (2010). The six core elements of Business Process Management. In vom Brocke, J. and Rosemann, M., eds., Handbook on Business Process Management 1. Berlin; Heidelberg: Springer, pp. 107–122.Google Scholar
Speer, S. A. (2002). ‘Natural’ and ‘contrived’ data: a sustainable distinction? Discourse Studies, 4(4), 511–525.Google Scholar
Tsoukas, H. and Chia, R. (2002). On organizational becoming: Rethinking organizational change. Organization Science, 13(5), 567–582.CrossRefGoogle Scholar
Turner, S. F. and Rindova, V. P. (2018). Watching the clock: Action timing, patterning, and routine performance. Academy of Management Journal, 61(4), 1253–1280.Google Scholar
van der Aalst, W. M. P. (2002). Making work flow: On the application of Petri Nets to Business Process Management. In Esparza, J. and Lakos, C.,eds., Application and Theory of Petri Nets 2002. ICATPN 2002. Lecture Notes in Computer Science, Vol. 2360. Berlin, Heidelberg: Springer, pp. 1–22.Google Scholar
van der Aalst, W. M. P. (2011). Process Mining: Discovery, Conformance and Enhancement of Business Processes, 2nd ed. Heidelberg: Springer.Google Scholar
van der Aalst, W. M. P. (2013). Business Process Management: A Comprehensive Survey. ISRN Software Engineering, 1–37.Google Scholar
van der Aalst, W. M. P., Adriansyah, A., De Medeiros, A. K. A., Arcieri, F., Baier, T., Blickle, T. … Wynn, M. (2011). Process mining manifesto. In Proceedings of the 9th International Conference on Business Process Management (BPM 2011) (pp. 169–194).Google Scholar
van der Aalst, W. M. P., ter Hofstede, A. H. and Weske, M. (2003). Business Process Management: A Survey. In International Conference on Business Process Management (BPM 2003).Google Scholar
Volkoff, O., Strong, D. M. and Elmes, M. B. (2007). Technological embeddedness and organizational change. Organization Science, 18(5), 832–848.Google Scholar
vom Brocke, J. and Mendling, J., eds. (2018). Business Process Management Cases. Cham: Springer International Publishing.Google Scholar
vom Brocke, J., Zelt, S. and Schmiedel, T. (2016). On the role of context in Business Process Management. International Journal of Information Management, 36(3), 486–495.Google Scholar
Wurm, B. (2018). Patterns of stability and change in business processes. In Proceedings of the 9th International Workshop on Enterprise Modeling and Information Systems Architectures (EMISA 2018), pp. 21–28.Google Scholar
Wurm, B., Goel, K., Bandara, W. and Rosemann, M. (2019). Design patterns for business process individualization. In 17th International Conference on Business Process Management (BPM 2019), pp. 370–385.Google Scholar
Wurm, B., Schmiedel, T., Mendling, J. and Fleig, C. (2018). Development of a Measurement Scale for Business Process Standardization. In 26th European Conference on Information Systems (ECIS 2018).Google Scholar
Yeshchenko, A., Di Ciccio, C., Mendling, J. and Polyvyanyy, A. (2019). Comprehensive process drift detection with visual analytics. In Laender, A., Pernici, B., Lim, E. and de Oliveira, J., eds., International Conference on Conceptual Modeling (ER 2019). Lecture Notes in Computer Science, vol. 11788. Cham: Springer, pp. 119–135.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×