254 Recker & Mendling Copyright © 2007, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Acknowledgment We gratefully acknowledge the fruitful contributions of our colleagues Michael Rosemann, Peter Green, Marta Indulska, Chris Manning, Petia Wohed, Wil van der Aalst, Arthur ter Hofstede, and Marlon Dumas to the evaluations of BPMN and BPEL by means of representation theory and work-ow patterns. Furthermore, we would like to thank Kristian Bisgaard Lassen and Uwe Zdun for the joint effort toward the identication of transformation strategies. References Andrews, T., Curbera, F., Dholakia, H., Goland, Y., Klein, J., Leymann, F., et al. (2003). Business process execution language for Web services: Version 1.1. Retrieved February 10, 2006, from http://xml.coverpages. org/BPELv11-May052003Final.pdf Bider, I., & Johannesson, P. (2002). Modeling dynamics of business processes: Key for building next generation of business information systems. In S. Spaccapietra, S. T. March, & Y. Kambayashi (Eds.), Conceptual model- ing: ER 2002 (Vol. 2503, pp. 7-9). Tampere, Finland: Springer. Bodart, F., Patel, A., Sim, M., & Weber, R. (2001). Should optional properties be used in conceptual modelling? A theory and three empirical tests. Information Systems Research, 12(4), 384-405. BPMI.org. (2004). Business process modeling notation (BPMN): Version 1.0. May 3, 20. Retrieved March 2, 2005, from http://www.bpmn.org/ BPMI.org. (2005). BPMN implementors and quotes. Retrieved February 24, 2006, from http://www.bpmn.org/BPMN_Supporters.htm BPMI.org & Object Management Group (OMG). (2006). Business process modeling notation specication: Final adopted specication. Retrieved February 20, 2006, from http://www.bpmn.org Bunge, M. A. (2003). Philosophical dictionary. New York: Prometheus Books. Curtis, B., Kellner, M. I., & Over, J. (1992). Process modeling. Communica- tions of the ACM, 35(9), 75-90. Lost in Business Process Model Translations 255 Copyright © 2007, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Davenport, T. H., & Short, J. E. (1990). The new industrial engineering: Information technology and business process redesign. Sloan Manage- ment Review, 31(4), 11-27. Dehnert, J., & van der Aalst, W. M. P. (2004). Bridging the gap between business models and workow specications. International Journal of Cooperative Information Systems, 13(3), 289-332. Dreiling, A., Rosemann, M., & van der Aalst, W. M. P. (2005). From con- ceptual process models to running workows: A holistic approach for the conguration of enterprise systems. 2005 Pacic Asia Conference on Information Systems, 363-376. 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. Ellison, M., & McGrath, G. M. (1998). Recording and analysing business processes: An activity theory based approach. Australian Computer Journal, 30(4), 146-152. Fischer, L. (Ed.). (2005). Workow handbook 2005. Lighthouse Point, FL: Future Strategies Inc. Gao, Y. (2006). BPMN-BPEL transformation and round trip engineering. Retrieved June 30, 2006, from http://www.eclarus.com/pdf/BPMN_ BPEL_Mapping.pdf Gemino, A., & Wand, Y. (2005). Complexity and clarity in conceptual modeling: Comparison of mandatory and optional properties. Data & Knowledge Engineering, 55(3), 301-326. Green, P., & Rosemann, M. (2000). Integrated process modeling: An onto- logical evaluation. Information Systems, 25(2), 73-87. Green, P., & Rosemann, M. (2004). Applying ontologies to business and systems modeling techniques and perspectives: Lessons learned. Journal of Database Management, 15(2), 105-117. Green, P., Rosemann, M., Indulska, M., & Manning, C. (in press). Candidate interoperability standards: An ontological overlap analysis. Data & Knowledge Engineering. Gruber, T. R. (1993). A translation approach to portable ontology specica- tions. Knowledge Acquisition, 5(2), 199-220. Guizzardi, G. (2005). Ontological foundations for structural conceptual models (Vol. 015). Enschede, the Netherlands: Telematica Instituut. 256 Recker & Mendling Copyright © 2007, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Hammer, M., & Champy, J. (1993). Reengineering the corporation: A mani- festo for business revolution. New York: Harpercollins. Jablonski, S., & Bussler, C. (1996). Workow management: Modeling con- cepts, architecture, and implementation. London: Thomson Computer Press. Katzenstein, G., & Lerch, F. J. (2000). Beneath the surface of organizational processes: A social representation. Framework for business process redesign. ACM Transactions on Information Systems, 18(4), 383-422. Keller, G., Nüttgens, M., & Scheer, A W. (1992). Semantische prozess- modellierung auf der grundlage “ereignisgesteuerter prozessketten (EPK)” (Working Paper No. 89). Saarbrücken, Germany: Institut für Wirtschaftsinformatik, Universität Saarbrücken. Kiepuszewski, B., ter Hofstede, A. H. M., & Bussler, C. (2000). On structured workow modelling. In B. Wangler & L. Bergmann (Eds.), Advanced information systems engineering: CAiSE 2000 (Vol. 1789, pp. 431-445). Stockholm, Sweden: Springer. Kiepuszewski, B., ter Hofstede, A. H. M., & van der Aalst, W. M. P. (2003). Fundamentals of control ow in workows. Acta Informatica, 39(3), 143-209. Kloppmann, M., Koenig, D., Leymann, F., Pfau, G., Rickayzen, A., von Rie- gen, C., et al. (2005). WS-BPEL extension for sub-processes: BPEL-SPE. Retrieved August 14, 2006, from https://www.sdn.sap.com/irj/servlet/ prt/portal/prtroot/docs/library/ Kung, C. H., & Sølvberg, A. (1986). Activity modeling and behavior model- ing of information systems. In T. W. Olle, H. G. Sol, & A. A. Verrijn- Stuart (Eds.), Information systems design methodologies: Improving the practice (pp. 145-171). Amsterdam: North-Holland. Mantell, K. (2005). From UML to BPEL: Model driven architecture in a Web services world. Retrieved June 30, 2006, from http://www-128. ibm.com/developerworks/webservices/library/ws-uml2bpel/ Mendling, J., Lassen, K. B., & Zdun, U. (2006). Transformation strategies between block-oriented and graph-oriented process modelling languages. In F. Lehner, H. Nösekabel, & P. Kleinschmidt (Eds.), Multikonferenz wirtschaftsinformatik 2006, Band 2 (pp. 297-312). Berlin, Germany: GITO-Verlag. Miers, D. (2003). The split personality of BPM. The BPMG Newsletter, 11(11), 1-22. Lost in Business Process Model Translations 257 Copyright © 2007, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Milton, S., & Kazmierczak, E. (2004). An ontology of data modelling lan- guages: A study using a common-sense realistic ontology. Journal of Database Management, 15(2), 19-38. Mylopoulos, J. (1992). Conceptual modelling and telos. In P. Loucopoulos & R. Zicari (Eds.), Conceptual modelling, databases, and CASE: An integrated view of information system development (pp. 49-68). New York: John Wiley & Sons. Nickerson, J. V., & zur Muehlen, M. (2006). The ecology of standards pro- cesses: Insights from Internet standard making. MIS Quarterly, 30(3), 467-488. Nysetvold, A. G., & Krogstie, J. (2005). Assessing business process modeling languages using a generic quality framework. CAiSE’05 Workshops, 1, 545-556. Porto, Portugal: FEUP. Ouyang, C., Dumas, M., Breutel, S., & ter Hofstede, A. H. M. (2006). Trans- lating standard process models to BPEL. In E. Dubois & K. Pohl (Eds.), Advanced information systems engineering: CAiSE 2006 (Vol. 4001, pp. 417-432). Luxembourg, Grand-Duchy of Luxembourg: Springer. Ouyang, C., van der Aalst, W. M. P., Dumas, M., & ter Hofstede, A. H. M. (2006). From BPMN process models to BPEL Web services. 4th Inter- national Conference on Web Services. Petri, C. A. (1962). Fundamentals of a theory of asynchronous information ow. In C. M. Popplewell (Ed.), IFIP Congress 62: Information Pro- cessing (pp. 386-390). Munich, Germany: North-Holland. Recker, J., Indulska, M., Rosemann, M., & Green, P. (2005). Do process modelling techniques get better? A comparative ontological analysis of BPMN. In Proceedings of the 16 th Australasian Conference on In- formation Systems. Recker, J., Indulska, M., Rosemann, M., & Green, P. (2006). How good is BPMN really? Insights from theory and practice. In Proceedings of the 14 th European Conference on Information Systems. Rosemann, M., & Green, P. (2002). Developing a meta model for the Bunge- Wand-Weber ontological constructs. Information Systems, 27(2), 75- 91. Rosemann, M., Recker, J., Indulska, M., & Green, P. (2006). A study of the evolution of the representational capabilities of process modeling grammars. In E. Dubois & K. Pohl (Eds.), Advanced information sys- 258 Recker & Mendling Copyright © 2007, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. tems engineering: CAiSE 2006 (Vol. 4001, pp. 447-461). Luxembourg, Grand-Duchy of Luxembourg: Springer. Russell, N., ter Hofstede, A. H. M., Edmond, D., & van der Aalst, W. M. P. (2005). Workow data patterns: Identication, representation and tool support. In L. M. L. Delcambre, C. Kop, H. C. Mayr, J. Mylopoulos, & Ó. Pastor (Eds.), Conceptual modeling: ER 2005 (Vol. 3716, pp. 353- 368). Klagenfurt, Austria: Springer. Russell, N., van der Aalst, W. M. P., ter Hofstede, A. H. M., & Edmond, D. (2005). Workow resource patterns: Identication, representation and tool support. In Ó. Pastor & J. Falcão e Cunha (Eds.), Advanced infor- mation systems engineering: CAiSE 2005 (Vol. 3520, pp. 216-232). Porto, Portugal: Springer. Siau, K. (2004). Informational and computational equivalence in compar- ing information modeling methods. Journal of Database Management, 15(1), 73-86. Smith, H., & Fingar, P. (2003). Business process management: The third wave. Tampa, FL: Meghan-Kiffer Press. Uschold, M., & Grüninger, M. (1996). Ontologies: Principles, methods and applications. The Knowledge Engineering Review, 11(2), 93-136. Van der Aalst, W. M. P., Dumas, M., ter Hofstede, A. H. M., & Wohed, P. (2002). Pattern-based analysis of BPML (and WSCI) (Tech. Rep. No. FIT-TR-2002-05). Brisbane, Australia: Queensland University of Technology. Van der Aalst, W. M. P., & ter Hofstede, A. H. M. (2005). YAWL: Yet another workow language. Information Systems, 30(4), 245-275. Van der Aalst, W. M. P., ter Hofstede, A. H. M., Kiepuszewski, B., & Barros, A. P. (2003). Workow patterns. Distributed and Parallel Databases, 14(1), 5-51. Wand, Y. (1996). Ontology as a foundation for meta-modelling and method engineering. Information and Software Technology, 38(4), 281-287. Wand, Y., Monarchi, D. E., Parsons, J., & Woo, C. C. (1995). Theoretical foundations for conceptual modelling in information systems Ddvelop- ment. Decision Support Systems, 15(4), 285-304. Wand, Y., & Weber, R. (1990). An ontological model of an information sys- tem. IEEE Transactions on Software Engineering, 16(11), 1282-1292. Lost in Business Process Model Translations 259 Copyright © 2007, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Wand, Y., & Weber, R. (1993). On the ontological expressiveness of infor- mation systems analysis and design grammars. Journal of Information Systems, 3(4), 217-237. Wand, Y., & Weber, R. (1995). On the deep structure of information systems. Information Systems Journal, 5(3), 203-223. Weber, R. (1997). Ontological foundations of information systems. Mel- bourne, Australia: Coopers & Lybrand & the Accounting Association of Australia and New Zealand. Weske, M., van der Aalst, W. M. P., & Verbeek, H. M. V. (2004). Advances in business process management. Data & Knowledge Engineering, 50(1), 1-8. White, S. A. (2005). Using BPMN to model a BPEL process. BPTrends, 3, 1-18. Wohed, P., van der Aalst, W. M. P., Dumas, M., & ter Hofstede, A. H. M. (2003). Analysis of Web services composition languages: The case of BPEL4WS. In I Y. Song, S. W. Liddle, T. W. Ling, & P. Scheuermann (Eds.), Conceptual modeling: ER 2003 (Vol. 2813, pp. 200-215). Chi- cago: Springer. Wohed, P., van der Aalst, W. M. P., Dumas, M., ter Hofstede, A. H. M., & Russell, N. (2006). On the suitability of BPMN for business process modelling. In Proceedings of the 4 th International Conference on Busi- ness Process Management. Yu, E. S. K., Mylopoulos, J., & Lespérance, Y. (1996). AI models for busi- ness-process reengineering. IEEE Expert: Intelligent Systems and Their Applications, 11(4), 16-23. Zhao, W., Hauser, R., Bhattacharya, K., Bryant, B. R., & Cao, F. (2006). Compiling business processes: Untangling unstructured loops in irre- ducible ow graphs. International Journal of Web and Grid Services, 2(1), 68-91. Zur Muehlen, M. (2004). Workow-based process controlling: Foundation, design and application of workow-driven process information systems. Berlin, Germany: Logos. Zur Muehlen, M., & Rosemann, M. (2004). Multi-paradigm process manage- ment. In Proceedings of the CAiSE’04 Workshops in Connection with the 16 th Conference on Advanced Information Systems Engineering (Vol. 2, pp. 169-175). 260 Nilakanta, Miller, & Zhu Copyright © 2007, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Abstract This chapter introduces theories and models used in organizational memory. As organizations continue to automate their business processes and collect explosive amounts of data, researchers in knowledge management need to confront new opportunities and new challenges. In this chapter, we provide a brief review of the literature in organizational memory management. Some of the core issues of organizational memory management include organi- zational context, retention structure, knowledge taxonomy and ontology, organizational learning, distributed cognition and communities of practice, and so forth. As new information technologies are available to the design and implementation of organizational memory, we further present a basic framework of theories and models, focusing on the technological components and their applications in organizational memory systems. Chapter X Theories and Models: A Brief Look at Organizational Memory Management Sree Nilakanta, Iowa State University, USA L. L. Miller, Iowa State University, USA Dan Zhu, Iowa State University, USA Theories and Models 261 Copyright © 2007, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Introduction Organizational memory, a crucial component of an organization’s knowledge ecosystem, plays a critical role in the overall performance and competitiveness of a business venture (March & Simon, 1958; Mort, 2001; Watson, 1998; Zhang, Tian, & Qi, 2006). In order to realize a benet or strategic advan- tage, however, this knowledge must be properly managed. Consequently, many organizations are using formal knowledge management practices to improve performance. Knowledge management is best described as a process in which information is transformed into actionable knowledge and made available to the user (Allee, 1997). Effective knowledge management enables businesses to avoid repeating prior mistakes, to ensure the continued use of best practices, and to draw on the collective wisdom of its employees, past and present. Organizational memory is the collection of historical corporate knowledge that is employed for current use through appropriate methods of gathering, organizing, rening, and disseminating the stored information and knowledge (Ackerman & Halverson, 2000; Nevo & Wand, 2005). The objectives of this chapter are to survey the organizational memory lit- erature and present a basic framework on organizational memory systems (OMSs) and applications while focusing our attention on IT-based organiza- tional memory. Research in organizational memory management deals with the creation, integration, maintenance, dissemination, and use of all kinds of knowledge within an organization (Alavi & Leidner, 1999; Cross & Baird, 2000). It is also confronted with new challenges because recent developments in information processing technologies have enhanced our ability to build the next generation of organizational memory management systems. Through our research studies, we found that much of the organizational memory is ignored or lost in the corporate collaborative processes in spite of the existence of several enterprise collaboration management tools. The consequence is that employees spend too much time re-creating common elements from online and off-line meetings, calendars, and various project-related activities. In the next section, we review the literature of organizational memory man- agement. Then we present a basic framework of technological components and their applications. Next we discuss some important research issues and future trends, and then conclude the chapter. 262 Nilakanta, Miller, & Zhu Copyright © 2007, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Organizational Memory Organizational memory has been described as corporate knowledge that represents prior experiences and is saved and shared by corporate users. It includes both stored records (e.g., corporate manuals, databases, ling sys- tems, etc.) and tacit knowledge (e.g., experience, intuition, beliefs; Nonaka & Takeuchi, 1995), and encompasses technical, functional, and social aspects of the work, the worker, and the workplace (Argote, McEvily, & Ray, 2003; Choy, Kwan, & Leong, 1999; Lee, Kim, Kim, & Cho, 1999). Organizational memory may be used to support decision making in multiple tasks and mul- tiple user environments, for example, in construction (Ozorhorn, Dikmen, & Birgonaul, 2005), in new product development (Akgun, Lynn, & Byrne, 2006), in machine learning and scheduling (Padman & Zhu, 2006), and in pursu- ing radical innovations (Johnson & Dilts, 2006). Walsh and Ungson (1991) refer to organizational memory as stored information from an organization’s history that can be brought to bear on present decisions. By their denition, organizational memory provides information that reduces transaction costs, contributes to effective and efcient decision making, and is a basis for power within organizations. Researchers and practitioners recognize organizational memory as an important factor in the success of an organization’s operations and its responsiveness to the changes and challenges of its environment (Huber, 1991; Huber, Davenport, & King, 1998). Information technologies contribute to enable automated organizational knowledge management systems in two ways: either by making recorded knowledge retrievable or by providing vehicles for knowledgeable workers to share information (Chen, Hsu, Orwig, Hoopes, & Nunamaker, 1994; Olivera, 2000; Zhao, 1998). Explicitly dispersing an organization’s knowledge through a variety of retention facilities (e.g., network servers, distributed databases, intranets, etc.) can make the knowledge more accessible to its members. Stein and Zwass (1995) suggest IT strategies can be used to maintain an extensive record of processes (through what sequence of events?), rationale (why?), context (under what circumstances?), and outcomes (how well did it work?). The availability of advanced information technologies increases the communicating and decision-making options for potential users. Sandoe, Croasdell, Courtney, Paradice, Brooks, and Olfman (1998) use Giddens’ (1984) denition of organizational memory to distinguish between discursive, practical, and reexive memory, and they treat IT-based organi- zational memory as discursive. They argue that although IT-based memory Theories and Models 263 Copyright © 2007, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. operates at a discursive level, IT makes the discursive process of remembering more efcient by reducing the costs and effort associated with the storage of and access to an organization’s memory. IT changes the balancing point in the trade-off between efciency and exibility, permitting organizations to be relatively more efcient for a given level of exibility. Another advan- tage of IT-based memory is the opportunity to provide a historical narrative (or rationale) for signicant organizational events that would otherwise be remembered in nondiscursive form. Furthermore, IT-based memory allows an organization to act in a rational manner through the discursive access to its major historical events and transformations. Additionally, Nevo and Wand (2005) note that IT-based organizational memory systems must deal not only with the location and source of memory, but also the context in which it occurs and is applicable. Finally, an OMS must address the tacit nature of some of the knowledge and the fact that the knowledge is volatile and has a nite life. Mandiwalla, Eulgem, Mould, and Rao (1998) dene an OMS to include a da- tabase management system (DBMS) that can represent more than transactional data, and an application that runs on top of the DBMS. They further describe the generic requirements of an OMS to include different types of memory, including how to represent, capture, and use organizational memory. Nemati, Steiger, Iyer, and Herschel (2002) illustrate that a knowledge warehouse combines three abilities: (a) an ability to efciently generate, store, retrieve, and, in general, manage explicit knowledge in various forms, (b) an ability to store, execute, and manage the analysis tasks and their supporting technolo- gies with minimal interaction and cognitive requirements from the decision maker, and (c) an ability to update the knowledge warehouse via a feedback loop of validated analysis output. The knowledge warehouse architecture has six major components: (a) the data or knowledge acquisition module, (b) the two feedback loops, (c) the extraction, transformation, and loading module, (d) a knowledge warehouse (storage) module, (e) the analysis workbench, and (f) a communications manager or user-interface module. Haseman and Nazareth (2005) use the term collective memory to represent organization memory. They show that by building capabilities to share meet- ing data, prior decisions, and external sources of data into the collective memory repository, group decisions are enhanced. A skilled facilitator helps with collecting, maintaining, and processing group decisions and outcomes managed through the VisionQuest commercial software. These decisions and other memory contents are weighted and ranked by the participants and [...]... modeling and development processes During the last years his major research area has been domain engineering Arnon has also gained extensive experience in developing software systems in industry and served as a member of software engineering groups that deal with system development problems Tuure Tuunanen received his doctoral degree in information systems science at the Helsinki School of Economics (Finland)... She is a research fellow at the Graduate School of Electronic Business and Software Industry, and is a PhD candidate in information systems science at the Helsinki School of Economics, Finland Her research interests include information systems development methods, stakeholder and end-user participation and collaboration throughout the information system life cycle, and multicustomer-multivendor information... teaching several courses about business process support, electronic commerce, and information systems development (ISD) methodologies Before joining the university, he worked for Accenture with the Communication and Hi-Tech Service Line His research interests include agile information systems development, the foundation and modeling of business services, and method engineering He is involved in consultancy... been the principal investigator in several major research projects funded by the Technological Development Center of Finland and the Academy of Finland His research papers have appeared in journals such as CACM, the Journal of AIS, Information and Management, and Information Systems, and over 30 of them have appeared in conference proceedings such as ICIS, HICSS, and CAiSE More information is located... assistant professor in the College of Business Administration at the University of Nebraska – Omaha (USA) His current research interests include the study of UML as an OO systems development tool, software engineering, and the impact of structural complexity upon the people and systems involved in the application development process Copyright © 2007, IGI Global Copying or distributing in print or electronic... knowledge systems, process analysis and redesign, and the development of management information He is active in editing international journals and has published many articles Arnon Sturm is a faculty member at Ben-Gurion University of the Negev (Israel) His research focuses on software engineering issues, in particular, Copyright © 2007, IGI Global Copying or distributing in print or electronic forms... interests include conceptual modeling, modeling languages and techniques for analysis and design, domain analysis, and development processes Her work has been published in journals and international conference proceedings Copyright © 2007, IGI Global Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited About the Contrbutors  Matti Rossi is an acting... Economics (Finland) in 2005 His current research interests lie in the area of IS development methods and processes, requirements engineering, and the convergence of IS and marketing disciplines in design He is currently a senior lecturer at The University of Auckland Business School His research has been published in Information & Management, Journal of Database Management, Journal of Information Technology... Operations Research, and others Her current research focuses on developing and applying intelligent and learning technologies to business and management Copyright © 2007, IGI Global Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited  Index Index A B abstract model 103 acceptance test 7 active domain 123–145 adaptation 58 Agile Manifesto 33, 35 Software. .. business process modeling, conceptual modeling, and requirements engineering Robert A Stegwee is professor of e-health architecture and standards at the Faculty of Business, Public Administration, and Technology of the University of Twente (The Netherlands) and a principal consultant with Capgemini Health Services, The Netherlands He was the former head of the Department of Business Information Systems . processing, reporting systems, and so forth. The ne- grained information gets compiled and aggregated into relevant warehouses and knowledge bases through composer and builder systems and interfaces. sen- sitivity, and interacts intelligently with users, letting them prole, lter, and categorize the complex information infrastructure. Research Issues and Future Trends Designing the ideal. with collecting, maintaining, and processing group decisions and outcomes managed through the VisionQuest commercial software. These decisions and other memory contents are weighted and ranked