Skip to main content
SpringerLink
Log in

Decision-enabled dynamic process management for networked enterprises

  • Published:
Information Systems Frontiers Aims and scope Submit manuscript

Abstract

Enterprises in today’s networked economy face numerous information management challenges, both from a process management perspective as well as a decision support perspective. While there have been significant relevant advances in the areas of business process management as well as decision sciences, several open research issues exist. In this paper, we highlight the following key challenges. First, current process modeling and management techniques lack in providing a seamless integration of decision models and tools in existing business processes, which is critical to achieve organizational objectives. Second, given the dynamic nature of business processes in networked enterprises, process management approaches that enable organizations to react to business process changes in an agile manner are required. Third, current state-of-the-art decision model management techniques are not particularly amenable to distributed settings in networked enterprises, which limits the sharing and reuse of models in different contexts, including their utility within managing business processes. In this paper, we present a framework for decision-enabled dynamic process management that addresses these challenges. The framework builds on computational formalisms, including the structured modeling paradigm for representing decision models, and hierarchical task networks from the artificial intelligence (AI) planning area for process modeling. Within the framework, interleaved process planning (modeling), execution and monitoring for dynamic process management throughout the process lifecycle is proposed. A service-oriented architecture combined with advances from the semantic Web field for model management support within business processes is proposed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Backstrom, C. (1998). Computational aspects of reordering plans. Journal of Artifical Intelligence Research, 9, 99–137.

    Google Scholar 

  • Bae, H., & Seo, Y. (2007). BPM-based integration of supply chain process modeling, executing and monitoring. International Journal of Production Research, 45(11), 2545–2566.

    Google Scholar 

  • Basu, A., & Blanning, R. W. (1994). Model integration using metagraphs. Information Systems Research, 5(3), 195–218.

    Article  Google Scholar 

  • Basu, A., & Blanning, R. W. (1999). Metagraphs in workflow support systems. Decision Support Systems, 25(3), 199–208.

    Article  Google Scholar 

  • Bhargava, H. K., Krishnan, R., & Muller, R. (1997). Decision support on demand: emerging electronic markets for decision technologies. Decision Support Systems, 19, 193–214.

    Article  Google Scholar 

  • Bider, I., & Johannesson, P. (2005). Guest Editorial: Special Issue on Goal-oriented Business Process Modelling. Business Process Management Journal, 11(6), 621–623.

    Google Scholar 

  • Blanning, R. W. (1993). Model management systems: an overview. Decision Support Systems, 9(1), 9–18.

    Article  Google Scholar 

  • Chang, A.-M., Holsapple, C. W., & Whinston, A. B. (1993). Model management issues and directions. Decision Support Systems, 9(1), 19–37.

    Article  Google Scholar 

  • Chari, K. (2002). Model composition using filter spaces. Information Systems Research, 13(1), 15–35.

    Article  Google Scholar 

  • Clark, A., & Scarf, H. (1960). Optimal policies for a multi-echelon inventory problem. Management Science, 6, 475–490.

    Article  Google Scholar 

  • Cohen, M. A., & Lee, H. L. (1998). Strategic analysis of integrated production and distribution system. Operations Research, 36, 216–228.

    Article  Google Scholar 

  • Deokar, A. V., Madhusudan, T., Briggs, R. O., & Nunamaker Jr., J. F. (2004). A structured approach to designing interleaved workflow and groupware tasks. Paper presented at the Americas Conference of Information Systems (AMCIS ‘04), New York, NY.

  • Dhar, V., & Jarke, M. (1993). On modeling processes. Decision Support Systems, 9(1), 39–49.

    Article  Google Scholar 

  • Dolk, D. R. (2000). Integrated model management in the data warehouse era. European Journal of Operational Research, 122(2), 199–218.

    Article  Google Scholar 

  • Dolk, D. R., & Kottemann, J. E. (1993). Model integration and a theory of models. Decision Support Systems, 9(1), 51–63.

    Article  Google Scholar 

  • Dumas, M., van der Aalst, W. M. P., & ter Hofstede, A. H. M. (Eds.). (2005). Process Aware Information Systems: Bridging People and Software through Process Technology. Hoboken, NJ: John Wiley & Sons, Inc.

  • El-Gayar, O. F., & Tandekar, K. (2007). An XML-based schema definition for model sharing and reuse in a distributed environment. Decision Support Systems, 43, 791–808.

    Article  Google Scholar 

  • Ezechukwu, O. C., & Maros, I. (2003). OOF: Open Optimization Framework (Departmental Technical Report No. 2003/7): Department of Computing, Imperial College London.

  • Ferguson, D. F., & Stockton, M. L. (2005). Service-oriented architecture: programming model and product architecture. IBM Systems Journal, 44(4), 753–780.

    Article  Google Scholar 

  • Geoffrion, A. M. (1987). An introduction to structural modeling. Management Science, 33(5), 547–588.

    Article  Google Scholar 

  • Geoffrion, A. M., & Krishnan, R. (2003a). E-business and management science: mutual impacts (part 1 of 2). Management Science, 49(10), 1275–1286.

    Article  Google Scholar 

  • Geoffrion, A. M., & Krishnan, R. (2003b). E-business and management science: mutual impacts (Part 2 of 2). Management Science, 49(11), 1445–1456.

    Article  Google Scholar 

  • Ghallab, M., Nau, D., & Traverso, P. (2004). Automated planning: Theory and practice. San Francisco: Kaufmann.

    Google Scholar 

  • Huh, S. Y., & Kim, H. M. (2004). A real-time synchronization mechanism for collaborative model management. Decision Support Systems, 37(3), 315–330.

    Google Scholar 

  • Huh, S. Y., Chung, Q. B., & Kim, H. M. (2000). Collaborative model management in departmental computing. INFOR, 38(4), 373–389.

    Google Scholar 

  • Iyer, B., Shankaranarayanan, G., & Lenard, M. L. (2005). Model management decision environment: a Web service prototype for spreadsheet models. Decision Support Systems, 40(2), 283–304.

    Article  Google Scholar 

  • Keeney, R. L. (1994). Creativity in decision making with value-focused thinking. Sloan Management Review, 35(4), 33–41.

    Google Scholar 

  • Keeney, R. L. (1996). Value-focused thinking: Identifying decision opportunities and creating alternatives. European Journal of Operational Research, 92(3), 537–549.

    Article  Google Scholar 

  • Kim, H. (2001). An XML-based modeling language for the open interchange of decision models. Decision Support Systems, 31(4), 429–441.

    Article  Google Scholar 

  • Konsynski, B., & Sprague, R. H. (1986). Future research directions in model management. Decision Support Systems, 2(1), 103–109.

    Article  Google Scholar 

  • Kopecký, J., Vitvar, T., Bournez, C., & Farrell, J. (2007). SAWSDL: Semantic Annotations for WSDL and XML Schema. IEEE Internet Computing, 11(6), 60–67.

    Article  Google Scholar 

  • Kottemann, J. E., & Dolk, D. R. (1992). Model integration and modeling languages: a process perspective. Information Systems Research, 3(1), 1–16.

    Article  Google Scholar 

  • Kumar, A., & Zhao, J. L. (1999). Dynamic routing and operational controls in workflow management systems. Management Science, 45(2), 253–272.

    Article  Google Scholar 

  • Liang, T.-P., & Konsynski, B. R. (1993). Modeling by analogy: use of analogical reasoning in model management systems. Decision Support Systems, 9(1), 113–125.

    Article  Google Scholar 

  • Madhusudan, T. (2007). A web services framework for distributed model management. Information Systems Frontiers, 9(1), 9–27.

    Article  Google Scholar 

  • Madhusudan, T., & Uttamsingh, N. (2006). A declarative approach to composing web services in dynamic environments. Decision Support Systems, 41(2), 325–357.

    Article  Google Scholar 

  • Maier, R., Hadrich, T., & Peinl, R. (2005). Enterprise knowledge infrastructures. Berlin: Springer.

    Google Scholar 

  • Muhanna, W. A. (1993). An object-oriented framework for model management and DSS development. Decision Support Systems, 9(2), 217–229.

    Article  Google Scholar 

  • Muhanna, W. A., & Pick, R. A. (1994). Meta-modeling concepts and tools for model management: a systems approach. Management Science, 40(9), 1093–1123.

    Article  Google Scholar 

  • Narasimhan, R., & Mahapatra, S. (2004). Decision models in global supply chain management. Industrial Marketing Management, 33, 21–27.

    Article  Google Scholar 

  • Narasimhan, R., Talluri, S., & Mahapatra, S. (2003). A mathematical model for evaluating multi-factor bids for agile supply base configuration (Working paper).

  • Nau, D. S., Au, T.-C., Ilghami, O., Kuter, U., Munoz-Avila, H., Murdock, J. W., et al. (2005). Applications of SHOP and SHOP2. IEEE Intelligent Systems, 20(2), 34–41.

    Article  Google Scholar 

  • Nau, D. S., Au, T.-C., Ilghami, O., Kuter, U., Murdock, J. W., Wu, D., et al. (2003). SHOP2: an HTN planning system. Journal of Artifical Intelligence Research, 20, 379–404.

    Google Scholar 

  • Neiger, D., & Churilov, L. (2002). Towards decision-enabled business process modelling tools: From e-EPC to de-EPC. Paper presented at the Proceedings of the Australasian Conference on Information Systems (ACIS ’02).

  • Neiger, D., & Churilov, L. (2006). Intelligent decision support through synchronized decomposition of process and objective structures. Paper presented at the Proceedings of the 39th Hawaii International Conference on System Sciences (HICSS-39 ’06), Kauai, HI.

  • Nilsson, A., Tolis, C., & Nellborn, C. (1999). Perspectives on business process modelling: Understanding and changing organizations. Berlin: Springer.

    Google Scholar 

  • Papazoglou, M. P. (2008). Web services: Principles and technology. New York: Pearson-Prentice Hall.

    Google Scholar 

  • Paraskevopoulos, D., Karakitsos, E., & Rustem, B. (1991). Robust capacity planning under uncertainty. Management Science, 37, 787–800.

    Article  Google Scholar 

  • Revelle, C. S., & Laporte, G. (1996). The plant location problem: new models and research prospects. Operations Research, 44, 864–874.

    Article  Google Scholar 

  • Rolland, C., & Prakash, N. (2000). Bridging the gap between organizational needs and ERP functionality. Requirements Engineering, 5, 180–193.

    Article  Google Scholar 

  • Scheer, A.-W. (1999). ARIS—business process frameworks (3rd ed.). Berlin: Springer-Verlag.

    Book  Google Scholar 

  • Scheer, A.-W. (2000). ARIS—business process modelling (3rd ed.). Berlin: Springer.

    Book  Google Scholar 

  • Schuschel, H., & Weske, M. (2004). Triggering replanning in an integrated workflow planning and enactment system. In B. Andras, J. Demetrovics, & G. Gottlob (Eds.), Proceedings of the 8th East European Conference on Advances in Databases and Information Systems (ADBIS ’04) (Vol. 3255, pp. 322–335). Budapest: Springer-Verlag.

    Google Scholar 

  • Seila, A., Ceric, V., & Tadikamalla, P. (2003). Applied Simulation Modeling: Duxbury Press.

  • Shapiro, J. F. (2007). Modeling the supply chain (2nd ed.). Belmont: Duxbury.

    Google Scholar 

  • Sirin, E., Parsia, B., Wu, D., Hendler, J., & Nau, D. (2004). HTN planning for web service composition using SHOP2. Journal of Web Semantics, 1(4), 377–396.

    Article  Google Scholar 

  • Soffer, P. (2005). On the notion of flexibility in business processes. Paper presented at the Proceedings of CAiSE’05 Workshops, Workshop on Business Process Modeling, Design and Support (BPMDS ’05).

  • Stone, P., & Veloso, M. (1996). User-guided interleaving of planning and execution. In M. Ghallab & A. Milani (Eds.), New Directions in AI Planning (pp. 103–114). Burke, VA: IOS Press.

  • Swaminathan, J. M., & Tayur, S. R. (2003). Models for supply chains in e-business. Management Science, 49(10), 1387–1406.

    Article  Google Scholar 

  • Talluri, S. (2002). A buyer-seller game model for selection and negotiation of purchasing bids. European Journal of Operational Research, 143, 171–180.

    Article  Google Scholar 

  • Talluri, S., & Narasimhan, R. (2003). Vendor evaluation with performance variability: a max–min approach. European Journal of Operational Research, 146, 543–552.

    Article  Google Scholar 

  • Trkman, P., & McCormack, K. (2009). Supply chain risk in turbulent environments—a conceptual model for managing supply chain network risk. International Journal of Production Economics, 119(2), 247–258.

    Article  Google Scholar 

  • van der Aalst, W. M. P., & van Hee, K. (2002). Workflow Management: Models, Methods, and Systems. Cambridge, MA: MIT Press.

  • Weber, B., Sadiq, S., & Reichert, M. (2009). Beyond rigidity—dynamic process lifecycle support: a survey on dynamic changes in process-aware information systems. Computer Science—Research and Development, 23(2), 47–65.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dakota State University, Madison, SD, USA

    Amit V. Deokar & Omar F. El-Gayar

Authors
  1. Amit V. Deokar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Omar F. El-Gayar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amit V. Deokar.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Deokar, A.V., El-Gayar, O.F. Decision-enabled dynamic process management for networked enterprises. Inf Syst Front 13, 655–668 (2011). https://doi.org/10.1007/s10796-010-9243-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10796-010-9243-3

Keywords

Search

Navigation