Abstract
Socio-economic systems are dynamically complex, influenced by multiple agents, and characterized by accumulations, time delays, and nonlinearities. To best account for these characteristics on a detailed level, I use an overall case-study strategy and operationalize it with several methods combined into a multimethodology (Fig. 3.1). The case-study setting is specified in Sect. 4.3. The study can be positioned more towards the objective approach to social science.
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Notes
- 1.
Each research strategy has different characteristics regarding the kind of research question addressed, the extent of control a researcher has over behavioral events, and the focus on contemporary as opposed to historical events.
- 2.
While in English the term methodology is used for both of these meanings, the German language provides two different words: “Methodik” and “Methodologie.” Here, I refer to “Methodik.”
- 3.
A recent example of a study which combines methodologies is undertaken by Schwaninger & Groesser, (2012). They have used a systemic-cybernetic approach to understand an organizational change process and the organization’s path dependency in relation to organizational closure and autopoiesis. By this means, they are able to reap insights “that are more realistic by using methods that penetrate façades” (Starbuck 2010: 1398).
- 4.
The differentiation between messy problems and stylized problems is much discussed in the operational research literature (Ackoff, 1979; Jackson, 2006; Mingers, 2009; Rosenhead & Mingers, 2001); it is related to the difference between “soft-OR” and “hard-OR” (Lane, 2000; Lane & Oliva, 1998; Paucar-Caceres & Rodriguez-Ulloa, 2006), and to the divide between qualitative and quantitative research (Müller-Merbach, 2007; Srnka & Koeszegi, 2007).
- 5.
Mingers (2001) distinguishes four types of multimethodologies: (1) methodology combination, (2) methodology enhancement, (3) single-paradigm multimethodology, (4) and multi-paradigm multimethodology. Until today no clear categorization exists if a multimethodology belongs to the single- or the multi-paradigm category. This distinction is not relevant here. It is most fertile for this study when both methodologies are used in the combinatory mode; i.e., the strengths of the methodology of grounded theory and system dynamics modeling are leveraged optimally by using their respective methods most beneficially.
- 6.
With a hint to Kuhn (1996), one might argue that the methodologies used in this research belong to the same research paradigm. First, both methodologies are able to develop dynamic models and theories. And second, both methodologies explicitly use the nation of iteration for developing their models or theories. A difference might be that theory of the type of system dynamics are formal, quantified, and mathematically closed (Schwaninger & Groesser, 2008), whereas theories generated with the grounded theory methodology are formal, might be even quantified, but lack the characteristic of a mathematical closeness. However, this is one of the aspects where both of the selected methodologies can complement each other.
- 7.
A methodology which might be used as an alternative to grounded theory is “Soft Systems Methodology” (SSM) (Checkland, 2008). This methodology was not selected for three reasons: first, the effort to conduct a complete analysis with SSM is prohibitively high compared to the resources available. Second, the experts of the research project (more details in Sect. 4.3) participated on a voluntary basis; it is assumed that is would be difficult to convince participants to engage in a full SSM analysis without compensation. And third, the methodology of SSM is a powerful one, which requires a significant level of innovativeness of the participants. In achieving such a degree, other characteristics of the participants which are more relevant to this study’s success might suffer; for instance, it was assumed that it would not be possible to convince professional building owners with a lower degree of innovativeness to participate in the study.
- 8.
The methodology of grounded theory was originated by Glaser and Strauss in the 1960s (Glaser & Strauss, 1967a). In the preceding years, two different schools of grounded theory have emerged (Punch, 2005): the Glaserian approach (Glaser, 1992) and the Straussian approach (Strauss, 1987); Juliet Corbin has supported Strauss from the early 1990s (Strauss & Corbin, 1990). Glaser’s approach emphasizes that the coding scheme—a coding heuristic—must emerge exclusively from the analysis of empirical evidence. Strauss and Corbin favor the application of a predefined coding scheme with such categories as phenomena, context conditions, causal relations, intervening conditions, actions strategies, and consequences (Corbin & Strauss, 2008; Strauss & Corbin, 1990). In addition, Strauss and Corbin allow for the explicit appreciation of existing theories in advance of the coding and analysis; in Glaser’s version, existing models and theories come in only after the analysis phase. The discussion of the unbiased perception of empirical evidence will not be elaborated here; the interested reader turn to further references (e.g., Glaser, 1978). I thank Prof. Dr. Katja Mruck and Prof. Dr. Günter Mey (both at the University of Berlin, Germany) for pointing out this small but significant difference between the two schools.
- 9.
Other methods, e.g., writing memos, are not elaborated here. See Strauss and Corbin (1998) for details.
- 10.
Theoretical sampling is also known as “handy sampling” (Carberry, 1971).
- 11.
Other purposes of the application of simulation are prediction of future conditions, performance improvement, training of participants, entertainment, education of students, and proof of conceptual elaborations (Axelrod, 2005).
- 12.
The deterministic nature of the differential equation-based methodologies can be diluted by the introduction of stochastic elements. I have applied this where necessary for model validation and policy analysis.
- 13.
The reflection about the adequacy of system dynamics as simulation methodology for this research resulted in the consideration of agent-based modeling (Epstein & Axtell, 1996). Agent-based modeling shares many of the strengths of the system dynamics methodology (Rahmandad & Sterman, 2008); but it lacks, among other things, the important characteristics of white-box modeling and the full-capacity of an elaborated validation methodology. Research has attempted to combine both methodologies to overcome their respective shortcomings (Größler, Stotz, & Schieritz, 2003; Schieritz, 2004; Schieritz & Milling, 2003; Scholl, 2001). Given that this research is still methodologically underdeveloped, I have rejected using agent-based modeling here.
- 14.
Sterman (2000) provides a basic compendium on the system dynamics modeling approach.
- 15.
These methods could be clustered differently. Behavior-over-time graphs, reference modes, and causal loop diagrams are methods of system dynamics methodology which formalize and represent system content; expert workshops, group model building, and interviews are foremost procedural methods. Because of the marginal additional insights for this study, I do not elaborate these dimensions.
- 16.
One alternative to the cognitive mapping interview style would be narrative interviews using interview guidelines. I see this method as being unable to deliver the additional benefits of the cognitive mapping interview method compared to the gain in reliability because of the ex-post coding of the material. I thank Dr. Jan Kruse (University of Freiburg, Germany, specialist in interview methods) for pointing out that the mindset of the interviewer in conducting narrative interviews influences the results regardless of the interview method used (personal communication).
- 17.
I thank Ms. Stephanie Geisshüsler for her support during the cognitive mapping interviews. In addition, I thank the Interfaculty Centre for General Ecology at the University of Bern for financial support that enabled us to conduct these interview situations.
- 18.
http://www.banxia.com/dexplore/index.html. I thank the Interfaculty Centre for General Ecology at the University of Bern for granting me access to this software.
- 19.
The summary of the major interviewing principles is provided upon request.
- 20.
More formalized: δY/δX > 0 (positive link); δY/δX < 0 (negative link).
- 21.
- 22.
A technique which is similar to cognitive mapping and causal loop diagrams is the “structural elicitation approach” (Spevacek, 1999). I did not choose this method because the method does not have advantages relative to the methods selected, and has most often been used only in psychology, not in the management sciences.
- 23.
The interview guidelines for the interviews phase are included in the Appendix (Chap. VII). The original language of the guidelines was German. The guidelines have been translated into English for this book; the interview documents are in German.
- 24.
I thank the project team which consisted of Dr. Silvia Ulli-Beer, Dr. Susanne Bruppacher, and Prof. Dr. Ruth Kaufmann-Hayoz. The design of each of four workshops was customized to the current state of the research project. The details of the workshops are not provided here, to protect the personal identities of participants. Contact the author for further information.
- 25.
Already Forrester (1961) has acknowledged the importance of facilitated decision modeling. I thank Prof. Dr. David Lane (London School of Economics, UK) for bringing this to my attention.
- 26.
Schwaninger (1997) has established a “paradoxes framework” which could also be used to position the book in the field of philosophy of science. He differentiates the dimensions of the type of modeling (from qualitative to quantitative modeling), the level of rationality (from conceptual to communicational rationality), and the Weltanschauung (from objectivistic to subjectivistic worldview).
- 27.
For reasons of simplification, I consider the book as being one integrated entity for which a position on the four continuums can be defined, even though different methodologies and methods are used: qualitative explorative interviews, statistical data analysis, grounded theory, and simulation modeling.
References
Ackoff, R. L., & Emery, F. E. (1972). On purposeful systems. Chicago: Aldine.
Ackoff, R. L. (1979). The future of operations research is past. Journal of the Operational Research Society, 30(2), 93–104.
Andersen, D. F., & Richardson, G. P. (1997). Scripts for group model building. System Dynamics Review, 13(2), 107–129.
Andersen, D. F., Richardson, G. P., & Vennix, J. A. M. (1997). Group model building: Adding more science to the craft. System Dynamics Review, 13(2), 187–201.
Andersen, D. F., Richardson, G. P., Ackermann, F., & Eden, C. (2007). Two group model building scripts that integrate systems thinking (using Vensim) into strategy workshops (using group explorer). Paper presented at the 25th international conference of the system dynamics society, Boston.
Anderson, V., & Johnson, L. (1997). Systems thinking basics: From concepts to causal loops. Cambridge, MA: Pegasus Communications.
Arrow, K. J. (1951). Mathematical models in the social sciences. In D. Lerner & H. J. Laswell (Eds.), The policy sciences (pp. 129–154). Standford, CA: Stanford University Press.
Astley, W. G., & Van de Ven, A. H. (1983). Central perspectives and debates in organization theory. Administrative Science Quarterly, 28(2), 245–273.
Axelrod, R. (1976). Structure of decisions: The cognitive maps of political elites. Princeton, NJ: Princeton University Press.
Axelrod, R. (1997). The complexity of cooperation, agent-based models of competition and collaboration. Princeton, NJ: Princeton University Press.
Axelrod, R. (2005). Advancing the art of simulation in the social sciences. In J.-P. Rennard (Ed.), Handbook of research on nature inspired computing for economy and management. Hershey, PA: Idea Group.
Balci, O. (1994). Validation, verification and testing techniques throughout the life cycle of a simulation study. Annals of Operations Research, 53(1), 121–173.
Bansal, P., & Roth, K. (2000). Why companies go green: A model of ecological responsiveness. Academy of Management Journal, 43(4), 717–736.
Barlas, Y., & Carpenter, S. (1990). Philosophical roots of model validation: Two paradigms. System Dynamics Review, 6(2), 148–166.
Barlas, Y. (1996). Formal aspects of model validity and validation in system dynamics. System Dynamics Review, 12(3), 183–210.
Bass, F. M. (1969). New product growth for model consumer durables. Management Science, 15(5), 215–227.
Bass, F. M. (1980). The relationship between diffusion rates, experience curves, and demand elasticities for consumer durable technological innovations. Journal of Business, 53(3), S51–S67.
Bernard, R. H. (2000). Social research methods: Quantitative and qualitative approaches. Thousand Oaks, CA/London/New Delhi, India: Sage Publications.
Bogner, A., Littig, B., & Menz, W. (Eds.). (2005). Das experteninterview: Theorie, methode, anwendung. Stuttgart, Germany: VS Verlag für Sozialwissenschaften.
Bortz, J., & Döring, N. (2002). Forschungsmethoden und Evaluation für Human und Sozialwissenschaftler (3rd ed.). Berlin, Germany: Springer.
Bougon, M. G. (1990). Congregate cognitive maps: A unified dynamic theory of organization and strategy. Journal of Management Studies, 29(3), 369–389.
Brauer, M. (2005). Resource allocation in divestments of high-technology business: A process perspective. Bamberg, Germany: Difo-Druck GmbH.
Brown, S. M. (1992). Cognitive mapping and repertory grids for qualitative survey research: Some comparative observations. Journal of Management Studies, 29(3), 287–307.
Bryson, J. M., Ackermann, F., Eden, C., & Finn, C. B. (2004). Visible thinking: Unlocking causal mapping for practical business results. London: Wiley.
Burell, G., & Morgan, G. (1979). Sociological paradigms and organisational analysis: Elements of the sociology of corporate life. Aldershot, UK: Gower.
Carberry, J. S. (1971). The new science of handy sampling. Cambridge, MA: Harvard University Press.
Chakravarthy, B., & White, R. E. (2001). Strategy process: Forming, implementing and changing strategies. In A. Pettigrew, H. N. Thomas, & R. Whittington (Eds.), Handbook of strategy and management (pp. 182–205). London: Sage Publications.
Checkland, P. (1981). System thinking, system practice. Chichester, UK: Wiley.
Checkland, P. (2008). Soft systems methodology: A 30-year retrospective. Chichester, UK: Wiley.
Clarke, I., & Mackaness, W. (2001). Management ‘Intuition’: An interpretative account of structure and content of decision schemas using cognitive maps. Journal of Management Studies, 38(2), 147–172.
Corbin, J., & Strauss, A. L. (2008). Basics of qualitative research. Thousand Oaks, CA: Sage Publications.
Craig, E. (Ed.). (1998). Routledge encyclopedia of philosophy: Volume 2: Brahman to Derrida. Oxford, UK: Oxford University Press.
Dattée, B., & Weil, H. B. (2007). Dynamics of social factors in technological substitutions. Technological Forecasting and Social Change, 74(5), 579–607.
Davis, J. P., Eisenhardt, K. M., & Bingham, C. B. (2007). Developing theory through simulation methods. Academy of Management Review, 32(2), 480–499.
Denzin, N. K., & Lincoln, Y. S. (Eds.). (2005). The Sage handbook of qualitative research (2nd ed.). Thousand Oaks, CA: Sage Publications.
Dieperink, C., Brand, L., & Vermeulen, W. (2004). Diffusion of energy-saving innovations in industry and the built environment: Dutch studies as inputs for a more integrated analytical framework. Energy Policy, 32(6), 773–784.
Dooley, K. (2002). Simulation research methods. In J. Baum (Ed.), Companion to organizations (pp. 829–848). London: Blackwell.
Eden, C. (1988). Cognitive mapping. European Journal of Operational Research, 36(1), 1–13.
Eden, C. (1992). On the nature of cognitive maps. Journal of Management Studies, 29(3), 261–265.
Eden, C. (1994). Cognitive mapping and problem structuring for system dynamics model building. System Dynamics Review, 10(4), 257–276.
Eden, C. (1998). Cognitive mapping and problem structuring for system dynamics model building. In R. G. Dyson & F. O’Brien (Eds.), Strategic development: Methods and models (pp. 227–242). Chichester, UK: Wiley.
Eisenhardt, K. M. (1989). Building theories from case-study research. Academy of Management Review, 14(4), 532–550.
Eisenhardt, K. M., & Graebner, M. E. (2007). Theory building from cases: Opportunities and challenges. Academy of Management Journal, 50(1), 25–32.
Epstein, J. M., & Axtell, R. (1996). Growing artificial societies: Social science from the bottom up. Washington, DC: Brookings Institution Press.
Ferlie, E., Fitzgerald, L., Wood, M., & Hawkins, C. (2005). The nonspread of innovations: The mediating role of professionals. Academy of Management Journal, 48(1), 117–134.
Fiol, C. M., & Huff, A. S. (1992). Maps for managers: Where are we? Where do we go from here? Journal of Management Studies, 29(3), 267–285.
Fisher, J. C., & Pry, R. H. (1971). A simple substitution model of technological change. Technological Forecasting and Social Change, 3(2), 75–88.
Ford, A. (1999). Modeling the environment: An introduction to system dynamic models of environmental systems. Washington, DC: Island Press.
Forrester, J. W. (1961). Industrial dynamics. Cambridge, MA: Productivity Press.
Forrester, J. W. (1968). Principles of systems. Cambridge, MA: MIT Press.
Forrester, J. W. (1971). Counterintuitive behavior of social systems. Technology Review, 73(3), 52–68.
Forrester, J. W., & Senge, P. M. (1980). Tests for building confidence in system dynamics models. In A. A. Legasto, J. W. Forrester, & J. M. Lyneis (Eds.), System dynamics: TIMS studies in the management sciences (Vol. 14). Amsterdam: North-Holland.
Forrester, J. W. (1992). Policies, decisions and information-sources for modeling. European Journal of Operational Research, 59(1), 42–63.
Gilbert, N., & Troitzsch, K. G. (2005). Simulation for the social scientist. Buckingham, PA: University Press.
Glaser, B. G., & Strauss, A. L. (1967a). The discovery of grounded theory. In B. G. Glaser & A. L. Strauss (Eds.), The discovery of grounded theory: Strategies for qualitative research (pp. 1–18). New York: Aldine De Gruyter.
Glaser, B. G., & Strauss, A. L. (Eds.). (1967b). The discovery of grounded theory: Strategies for qualitative research. New York: Aldine De Gruyter.
Glaser, B. G. (1978). Theoretical sensitivity: Advances in the methodology of grounded theory. Mill Valley, NY: Sociology Press.
Glaser, B. G. (1992). Basics of grounded theory analysis. Mill Valley, CA: Sociology Press.
Gonçalves, P. M., Hines, J. H., & Sterman, J. D. (2005). The impact of endogenous demand on push–pull production systems. System Dynamics Review, 21(3), 187–216.
Groesser, S. N., & Schwaninger, M. (2009). A validation methodology for system dynamics models. Paper presented at the 27th international conference of the system dynamics society, New Mexico.
Größler, A., Stotz, M., & Schieritz, N. (2003). A software interface between system dynamics and agent-based simulations - Linking Vensim and RePast. Paper presented at the 23 rd international conference of the system dynamics society, Atlanta GA.
Grübler, A. (1998). Technology and global change. Cambridge, UK: Cambridge University Press.
Hackney, R., Xu, H., & Ranchhod, A. (2006). Evaluating web services: Towards a framework for emergent contexts. European Journal of Operational Research, 173(3), 1161–1174.
Hall, R. (1993). A framework linking intangible resources and capabilities to sustainable competitive advantage. Strategic Management Journal, 14(8), 607–618.
Hall, R. I. (1976). A system pathology of an organization: The rise and fall of the old Saturday evening post. Administrative Science Quarterly, 21(2), 185–211.
Hanneman, R. A. (1988). Computer-assisted theory building: Modeling dynamic social systems. Newsbury Park, CA: Sage Publications.
Hardin, G. (1968). The tragedy of the commons. Science, 162(3859), 1243–1248.
Hegelund, A. (2005). Objectivity and subjectivity in the ethnographic method. Qualitative Health Research, 15(5), 647–668.
Hekkert, M. P., & Negro, S. O. (2009). Functions of innovation systems as a framework to understand sustainable technological change: Empirical evidence for earlier claims. Technological Forecasting and Social Change, 76(4), 584–594.
Hirschheim, R., & Klein, H. K. (1989). Four paradigms of information systems development. Communications of the ACM, 32(10), 1199–1216.
Homer, J. B. (1996). Why we iterate: Scientific modeling in theory and practice. System Dynamics Review, 12(1), 1–19.
Honderich, T. (Ed.). (2005). The Oxford companion to philosophy (Vol. 2). Oxford, UK: Oxford University Press.
Howick, S., Ackermann, F., & Andersen, D. (2006). Linking event thinking with structural thinking: Methods to improve client value in projects. System Dynamics Review, 22(2), 113–140.
Howick, S., & Ackermann, F. (2012). Mixing OR methods in practice: Past, present and future directions. European Journal of Operational Research, 215(3), 503–511.
Jackson, M. C. (1993). Social theory and operational research practice. Journal of the Operational Research Society, 44(6), 563–577.
Jackson, M. C. (2003). System thinking: Creative holism for managers. Chichester, UK: Wiley.
Jackson, M. C. (2006). Beyond problem structuring methods: Reinventing the future of OR/MS. Journal of the Operational Research Society, 57(7), 868–878.
Jupp, V. (2006). The Sage dictionary of social research methods. London: Sage Publications.
Kalev, A., Shenhav, Y., & De Vries, D. (2008). The state, the labor process, and the diffusion of managerial models. Administrative Science Quarterly, 53(1), 1–28.
Kim, D. H. (2000). Systems thinking tools. Waltham, MA: Pegasus Communications.
Kopainsky, B., & Luna-Reyes, L. F. (2008). Closing the loop: Promoting synergies with other theory building approaches to improve system dynamics practice. Systems Research and Behavioral Science, 25(4), 471–486.
Kuhn, T. S. (1996). The structure of scientific revolutions. Chicago, IL: Chicago University Press.
Lane, D. C. (2008). The emergence and use of diagramming in system dynamics: A critical account. Systems Research and Behavioral Science, 25(1), 3–23.
Lane, D. C., & Oliva, R. (1998). The greater whole: Towards a synthesis of system dynamics and soft systems methodology. European Journal of Operational Research, 107(1), 214–235.
Lane, D. C. (1999). Social theory and system dynamics practice. European Journal of Operational Research, 113(3), 501–527.
Lane, D. C. (2000). Should system dynamics be described as a ‘Hard’ or ‘Deterministic’ systems approach? Systems Research and Behavioral Science, 17(1), 3–22.
Lane, D. C. (2001a). Rerum cognoscere causas: Part II - opportunities generated by the agency/structure debate and suggestions for clarifying the social theoretic position of system dynamics. System Dynamics Review, 17(4), 293–309.
Lane, D. C. (2001b). Rerum cognoscere causas: Part I - How do the ideas of system dynamics relate to traditional social theories and the voluntarism/determinism debate? System Dynamics Review, 17(2), 97–118.
Lane, D. C., & Husemann, E. (2004). Movie marketing strategy formation with system dynamics: Toward a multi-disciplinary adoption/diffusion theory of cinema-going. Paper presented at the 22nd international conference of the system dynamics society, Oxford, England.
Lane, D. C., & Schwaninger, M. (2008). Theory building with system dynamics: Topic and research contributions. Systems Research and Behavioral Science, 25(4), 439–445.
Langley, A. (1999). Strategies for theorizing from process data. Academy of Management Review, 24(4), 691–710.
Leonard, A. (1997). Using models in sequence: A case study of a post-acquisition intervention. In J. Mingers & A. Gill (Eds.), Multimethodology: Theory and practice of combining management science methods (pp. 105–126). Chichester, UK: Wiley.
Locke, K. D. (2001). Grounded theory in management research. London: Sage Publications.
Luna-Reyes, L. F., & Andersen, D. L. (2003). Collecting and analyzing qualitative data for system dynamics: Methods and models. System Dynamics Review, 19(4), 271–296.
Luna-Reyes, L. F., Martinez-Moyano, I. J., Pardo, T. A., Cresswell, A. M., Andersen, D. F., & Richardson, G. P. (2006). Anatomy of a group model-building intervention: Building dynamic theory from case study research. System Dynamics Review, 22(4), 291–320.
Lyneis, J. M. (1982). Corporate planning and policy design: A system dynamics approach. Portland, OR: Productivity Press.
Madlener, R., & Wickart, M. (2004). Diffusion of cogeneration in Swiss industries: Economics, technical change, field of application and framework conditions. Energy and Environment, 15(2), 223–238.
Mahajan, V., & Schoeman, M. E. F. (1977). Generalized model for the time patterns of the diffusion process. IEEE Transactions on Engineering Management, 24(2), 12–18.
Mahajan, V., & Peterson, R. A. (1978). Innovation diffusion in a dynamic potential adopter population. Management Science, 24(15), 1589–1597.
Mahajan, V., Muller, E., & Srivastava, R. K. (1990). Determination of adopter categories by using innovation diffusion-models. Journal of Marketing Research, 27(1), 37–50.
Mahajan, V., & Muller, E. (1996). Timing, diffusion, and substitution of successive generations of technological innovations: The IBM mainframe case. Technological Forecasting and Social Change, 51(2), 109–132.
Mahajan, V., Muller, E., & Wind, Y. (Eds.). (2000). New-product diffusion models. Boston: Kluwer Academic.
Malerba, F. (2002). Sectoral systems of innovation and production. Research Policy, 31(2), 247–264.
March, J. G., & Simon, H. A. (1976). Organizations (23rd ed.). New York: Wiley.
Markard, J., & Truffer, B. (2008a). Technological innovation systems and the multi-level perspective: Towards an integrated framework. Research Policy, 37(4), 596–615.
Markard, J., & Truffer, B. (2008b). Actor-oriented analysis of innovation systems: Exploring micro-meso level linkages in the case of stationary fuel cells. Technology Analysis and Strategic Management, 20(4), 443–464.
Martin, P. Y., & Turner, B. A. (1986). Grounded theory and organizational research. The Journal of Applied Behavioral Science, 22(2), 141–157.
McKenney, J. L. (1967). Critique of: Verification of computer simulation models. Management Science, 14(2), B-102–B-103.
Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis an expanded sourcebook (2nd ed.). Beverly Hills, CA: Sage Publications.
Milling, P., & Maier, F. H. (1996). Invention, Innovation und Diffusion: eine Simulationsanalyse des Managements neuer Produkte. Berlin, Germany: Duncker und Humblot.
Mingers, J., & Gill, A. (Eds.). (1997). Multimethodology: Theory and practice of combining management science methods. Chichester, UK: Wiley.
Mingers, J. (2001). Multimethodology - mixing and matching methods. In J. Rosenhead & J. Mingers (Eds.), Rational analysis for a problematic world revisited: Problem structuring methods for complexity, uncertainty and conflict (2nd ed., pp. 289–309). Chichester, UK/New York/Weinheim, Germany/Brisbane, Australia/Singapore, Singapore/Toronto, ON: Willey.
Mingers, J., & Rosenhead, J. (2004). Problem structuring methods in action. European Journal of Operational Research, 152(3), 530–554.
Mingers, J. (2009). Taming hard problems with soft OR. Analyticsmagazine.com (Spring): 26-30.
Mingers, J., Liu, W., & Meng, W. (2009). Using SSM to structure the identification of inputs and outputs in DEA. Journal of the Operational Research Society, 60(2), 168–179.
Mintzberg, H., & Lampel, J. (1999). Reflecting on the strategy process. Sloan Management Review, 40(3), 21–29.
Mintzberg, H. (2008). Strategy safari the complete guide through the wilds of strategic management (2nd ed.). Harlow, UK: Financial Times Prentice Hall.
Mitchell, M. (2009). Complexity: A guided tour. Oxford, UK: Oxford University Press.
Morgan, G. (1997). Images of organization. Thousand Oaks, CA: Sage Publications.
Müller-Merbach, H. (2007). The great divide: The division of the OR/MS community into “Mathematicians” and “Social Technologists” limits its overall success. OR/MS Today, 34(2), 20–21.
Müller, M. O., Groesser, S. N., & Ulli-Beer, S. (2012). How do we know who to include in transdisciplinary research? Toward a method for the identification of experts. European Journal of Operational Research, 216(2), 495–502.
Munro, I., & Mingers, J. (2002). The use of multimethodology in practice - results of a survey of practitioners. Journal of the Operational Research Society, 53(4), 369–378.
O’Mahoney, J. (2007). The diffusion of management innovations: The possibilities and limitations of memetics. Journal of Management Studies, 44(8), 1324–1348.
Opp, K.-D. (2008). Methodologie der Sozialwissenschaften Einführung in Probleme ihrer Theorienbildung und praktischen Anwendung (7th ed.). Opladen, Germany: Westdeutscher Verlag.
Paucar-Caceres, A., & Rodriguez-Ulloa, R. (2006). An application of Soft Systems Dynamics Methodology (SSDM). Journal of the Operational Research Society, 58(6), 701–713.
Perlow, L. A., & Repenning, N. P. (2009). The dynamics of silencing conflict. Research in Organizational Behavior, 29(2), 195–223.
Ponterotto, J. G. (2005). Qualitative research in counseling psychology: A primer on research paradigms and philosophy of science. Journal of Counseling Psychology, 52(2), 126–136.
Punch, K. F. (2005). Introduction to social research: Quantitative and qualitative approaches. London/Thousand Oaks, CA/New Delhi, Delhi: Sage Publications.
Rahmandad, H., & Sterman, J. (2008). Heterogeneity and network structure in the dynamics of diffusion: Comparing agent-based and differential equation models. Management Science, 54(5), 998–1014.
Repenning, N. P. (2001). Understanding fire fighting in new product development. Journal of Product Innovation Management, 18(5), 285–300.
Repenning, N. P., Goncalves, P., & Black, L. J. (2001). Past the tipping point: The persistence of firefighting in product development. California Management Review, 43(4), 44–54.
Repenning, N. P. (2002). A simulation-based approach to understanding the dynamics of innovation implementation. Organization Science, 13(2), 109–127.
Repenning, N. P., & Sterman, J. D. (2002). Capability traps and self-confirming attribution errors in the dynamics of process improvement. Administrative Science Quarterly, 47(2), 265–295.
Richardson, G. P., & Pugh, A. L., III. (1981). Introduction to system dynamics modeling with DYNAMO. Cambridge, MA: Productivity Press.
Richardson, G. P. (1986). Problems with causal-Loop diagrams (1976). System Dynamics Review, 2(2), 158–170.
Richardson, G. P., & Andersen, D. F. (1995). Teamwork in group model building. System Dynamics Review, 11(2), 113–137.
Richardson, G. P. (1997). Problems in causal loop diagrams revisited. System Dynamics Review, 13(3), 247–252.
Richardson, G. P. (1999). Feedback thought in social science and systems theory. Waltham, MA: Pegasus Communications.
Richmond, B. M. (1997). The “Strategic Forum”: Aligning objectives strategy and process. System Dynamics Review, 13(2), 131–148.
Robinson, S. (2007). Conceptual modelling for simulation part II: A framework for conceptual modelling. Journal of the Operational Research Society, 59(3), 291–304.
Rosenhead, J., & Mingers, J. (Eds.). (2001). Rational analysis for a problematic world revisited: Problem structuring methods for complexity, uncertainty and conflict (2nd ed.). Chichester, UK/New York/Weinheim, Germany/Brisbane, Australia/Singapore, Singapore/Toronto, ON: Wiley.
Rudolph, J. W., & Repenning, N. P. (2002). Disaster dynamics: Understanding the role of quantity in organizational collapse. Administrative Science Quarterly, 47(1), 1–30.
Sargent, R. G. (1985). An expository on verification and validation of simulation models, Proceedings of the 17th conference on winter simulation. San Francisco, CA: Winter simulation conference
Sargent, R. G. (2008). Verification and validation of simulation models, Proceedings of the 40th conference on winter simulation. Miami, FL: Winter simulation conference
Sastry, M. A. (1997). Problems and paradoxes in a model of punctuated organizational change. Administrative Science Quarterly, 42(2), 237–275.
Schaffernicht, M., & Groesser, S. N. (2011). Comparison of mental models: Development of a comprehensive method. European Journal of Operational Research, 210(1), 57–67.
Schieritz, N., & Milling, P. M. (2003). Modeling the forest or modeling the trees: A comparison of system dynamics and agent-based simulation. Paper presented at the 21st international conference of the system dynamics society, New York City.
Schieritz, N. (2004). Exploring the agent vocabulary: Emergence and evolution in system dynamics. Paper presented at the 22nd International Conference of the system dynamics society, Oxford, England.
Scholl, H. J. (2001). Looking across the fence: Comparing findings from SD modeling efforts with those of other modeling techniques. Paper presented at the 19th international conference of the system dynamics society, Atlanta. GA
Schwaninger, M. (1997). Integrative systems methodology: Heuristics for requisite variety. International Transactions in Operational Research, 4(2), 109–123.
Schwaninger, M., & Groesser, S. N. (2008). Model-based theory-building with system dynamics. Systems Research and Behavioral Science, 25(4), 447–465.
Schwaninger, M. (2009a). Intelligent organizations: Powerful models for systemic management (2nd ed.). Berlin/Heidelberg, Germany: Springer.
Schwaninger, M. (2009b). System dynamics in the evolution of the systems approach. In R. A. Meyers (Ed.), Encyclopedia of complexity and system science (pp. 8974–8986). Berlin, Germany/London/Paris: Springer.
Schwaninger, M., & Groesser, S. N. (2009). System dynamics modeling: Validation for quality assurance. In Encyclopedia of complexity and system science. Berlin, Germany/London/Paris: Springer.
Schwaninger, M., & Groesser, S. N. (2012). Operational closure and self-reference: On the logic of organizational change. Systems Research and Behavioral Science, 29(4), 1–28.
Senge, P. M. (1990). The fifth discipline: The art and practice of the learning organization. New York: Currency & Doubleday.
Siggelkow, N. (2007). Persuasion with case studies. Academy of Management Journal, 50(1), 20–24.
Snijders, T. A. B., & Bosker, R. J. (1999). Multilevel analysis: An introduction to basic and advanced multilevel modeling. London: Sage Publications.
Spevacek, G. (1999). Struktur-Lege-Technik: Lernen mit Bildern in Texten in Abhängigkeit von bereichsspezifischem Wissen. Hamburg, Germany: Dr. Kovač.
Srnka, K. J., & Koeszegi, S. T. (2007). From words to numbers: How to transform qualitiative data into meaningful quantiative results. Schmalenbach Business Review, 59(1), 29–57.
Stake, R. E. (1996). The art of case study research. Thousand Oaks, CA: Sage Publications.
Starbuck, W. H. (1983). Computer simulation of human behavior. Behavioral Science, 28(2), 154–165.
Starbuck, W. H. (2010). What makes a paper influential and frequently cited? Journal of Management Studies, 47(7), 1394–1404.
Sterman, J. D. (1988). A Skeptic’s guide to computer models. In L. Grant (Ed.), Foresight and national decisions (pp. 133–169). Lanham, MD: University Press of America.
Sterman, J. D. (1989a). Misperceptions of feedback in dynamic decision-making. Organizational Behavior and Human Decision Processes, 43(3), 301–335.
Sterman, J. D. (1989b). Modeling managerial behavior - misperceptions of feedback in a dynamic decision-making experiment. Management Science, 35(3), 321–339.
Sterman, J. D., Repenning, N. P., & Kofman, F. (1997). Unanticipated side effects of successful quality programs: Exploring a paradox of organizational improvement. Management Science, 43(4), 503–521.
Sterman, J. D., & Wittenberg, J. (1999). Path dependence, competition, and succession in the dynamics of scientific revolution. Organization Science, 10(3), 322–341.
Sterman, J. D. (2000). Business dynamics: Systems thinking and modeling for a complex world. Boston: McGraw-Hill.
Sterman, J. D. (2002). All models are wrong: Reflections on becoming a systems scientist. System Dynamics Review, 18(4), 501–531.
Sterman, J. D. (2005). Operational and behavioral causes of supply chain instability. In O. Carranza & F. Villegas (Eds.), The Bullwhip effect in supply chains: A review in methods, components, and cases. Basingstoke, UK: Palgrave McMillan.
Sterman, J. D., Henderson, R., Beinhocker, E. D., & Newman, L. I. (2007). Getting big too fast: Strategic dynamics with increasing returns and bounded rationality. Management Science, 53(4), 683–696.
Stern, P. N. (1994). Eroding grounded theory. In J. M. Morse (Ed.), Critical issues in qualitative research methods (pp. 210–223). Salt Lake City, UT: Sage Publications.
Strauss, A. L. (1987). Qualitative analysis for social scientists. Cambridge, UK: Cambridge University Press.
Strauss, A. L., & Corbin, J. (1990). Basics of qualitative research: Techniques and procedures for developing grounded theory. Newbury Park, CA: Sage Publications.
Strauss, A. L., & Corbin, J. M. (Eds.). (1997). Grounded theory in practice. Thousand Oaks, CA: Sage Publications.
Strauss, A. L., & Corbin, J. M. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory (2nd ed.). Thousand Oaks, CA: Sage Publications.
Suddaby, R. (2006). From the editors: What grounded theory is not. Academy of Management Journal, 49(5), 633–642.
Swan, J., & Newell, S. (1994). Manager’s beliefs about factors affecting the adoption of technological innovation: A study using cognitive maps. Journal of Managerial Psychology, 9(2), 3–11.
Szmigin, I., & Foxall, G. (1998). Three forms of innovation resistance: The case of retail payment methods. Technovation, 18(6–7), 459–468.
Tashakkori, A. (2004). Handbook of mixed methods in social & behavioral research (2nd ed.). Thousand Oaks, CA: Sage Publications.
van de Ven, A. H., & Huber, G. P. (1990). Longitudinal field research methods for studying processes of organizational change. Organization Science, 1(3), 213–219.
Vaughan, D. (1990). Autonomy, interdependence, and social-control - NASA and the Space-Shuttle Challenger. Administrative Science Quarterly, 35(2), 225–257.
Vennix, J. A. M., Gubbels, J. W., Post, D., & Poppen, H. J. (1990). A structured approach to knowledge elicitation in conceptual model building. System Dynamics Review, 6(2), 194–208.
Vennix, J. A. M., Andersen, D. F., Richardson, G. P., & Rohrbaugh, J. W. (1992). Model-building for group decision support - issues and alternatives in knowledge elicitation. European Journal of Operations Research, 59(1), 28–41.
Vennix, J. A. M. (1996). Group model building: Facilitating team learning using system dynamics. Chichester, UK: Wiley.
Warren, K. (2004). Why has feedback systems thinking struggled to influence strategy and policy formulation? Suggestive evidence, explanations and solutions. Systems Research and Behavioral Science, 21(4), 331–347.
Warren, K. D., & Langley, P. A. (1999). The effective communication of system dynamics to improve insight and learning in management education. Journal of the Operational Research Society, 50(4), 396–404.
Webster. (1994). Webster’s new encyclopedic dictionary. New York: Black Dog & Levinthal.
Weick, K. E. (1993). The collapse of sensemaking in organizations - the Mann Gulch disaster. Administrative Science Quarterly, 38(4), 628–652.
Weil, H. B. (2007). Application of system dynamics to corporate strategy: An evolution of issues and frameworks. System Dynamics Review, 23(2–3), 137–156.
Wiener, N. (1948). Cybernetics: On control and communication in the animal and the machine. Cambridge, MA: MIT Press.
Wooldridge, M. J. (2009). An Introduction to multiagent systems (2nd ed.). Chichester, UK: Wiley.
Yin, R. K. (2003). Case study research. Beverly Hills, CA: Sage Publications.
Zeigler, B. P., Praehofer, H., & Kim, T. G. (2000). Theory of modeling and simulation (2nd ed.). San Diego, CA: Academic.
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Grösser, S.N. (2013). Research Design. In: Co-Evolution of Standards in Innovation Systems. Contributions to Management Science. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-2858-0_3
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