Bridging the gap between artificial market simulations and qualitative research in diffusion of innovation

Artificial markets (AMs) are an emerging form of agent-based simulation (ABS), in which agents represent individual consumers, firms, or industries interacting under simulated market conditions. The validity of the method depends on the ability of researchers to construct simulated agents that faithfully capture the key behavior of targeted entities. Without such a correspondence the simulation cannot be considered to be a valid representation of market dynamics. To date, no such correspondence has been established. Yet, for artificial markets to achieve their potential as a tool for marketing practice it is crucial that closer ties be forged with mainstream methods for consumer behavioral research, especially qualitative methods. The primary contribution of this article is a novel method combining qualitative marketing research (inductive case studies, grounded theory, and sequence analysis) and software engineering techniques to synthesize simulation-ready theories of consumer behavior. We provide a step-by-step explanation and a demonstrative example of theory-building from the consumer technology adoption domain. The outcome is a theory of consumer adoption behavior that is sufficiently precise and formal to be expressed in Unified Modeling Language (UML). The article concludes with a discussion of the limitations of the method, recommendations for its implementation in the study of diffusion of innovation (DOI) and suggestions for further research. The arguments and findings in this article that pertain to artificial markets can be generalized with respect to most agent-based simulations, including those applied to the study of diffusion of innovation. The results of an ABS of innovation diffusion cannot be relied upon unless the agents are based on a theory of adoption that grounded in empirical observations of the targeted entities — regardless of whether those entities are consumers, firms or industries. Qualitative research of adoption behavior is thus a useful precursor to successful agent-based approaches to studying the diffusion of innovations.

[1]  Bill McKelvey,et al.  Complexity Theory in Organization Science: Seizing the Promise or Becoming a Fad? , 1999 .

[2]  Chris Goldspink.  Methodological Implications Of Complex Systems Approaches to Sociality: Simulation as a foundation for knowledge , 2002, J. Artif. Soc. Soc. Simul..

[3]  Michael Agar,et al.  My Kingdom for a Function: Modeling Misadventures of the Innumerate , 2003, J. Artif. Soc. Soc. Simul..

[4]  Grant Mccracken.  The long interview , 1988 .

[5]  C. Brodsky.  The Discovery of Grounded Theory: Strategies for Qualitative Research , 1968 .

[6]  Keith S. Coulter,et al.  Interpreting Consumer Perceptions of Advertising: An Application of the Zaltman Metaphor Elicitation Technique , 2001 .

[7]  Charles M. Weber,et al.  Deciding to change: An event sequence analysis of consumer adoption behavior , 2009, PICMET '09 - 2009 Portland International Conference on Management of Engineering & Technology.

[8]  G. Nigel Gilbert,et al.  Simulation for the social scientist , 1999 .

[9]  Bruce Powel Douglass.  Real-Time UML , 2002, FTRTFT.

[10]  G. Löffler,et al.  Agent-based simulation of consumer behavior in grocery shopping on a regional level , 2007 .

[11]  Michael Agar,et al.  Agents in Living Color: Towards Emic Agent-Based Models , 2004, J. Artif. Soc. Soc. Simul..

[12]  E. Rogers.  Diffusion of Innovations , 1962 .

[13]  Sinan Si Alhir.  UML in a Nutshell , 1998 .

[14]  Gerald Zaltman,et al.  Using the Zaltman Metaphor Elicitation Technique to Understand Brand Images , 1994 .

[15]  R. Kozinets.  The Field behind the Screen: Using Netnography for Marketing Research in Online Communities , 2002 .

[16]  J. Rayport,et al.  Spark innovation through empathic design. , 1997, Harvard business review.

[17]  David Harel,et al.  On visual formalisms , 1988, CACM.

[18]  K. Eisenhardt.  Building theories from case study research , 1989, STUDI ORGANIZZATIVI.

[19]  Craig J Thompson.  Interpreting Consumers: A Hermeneutical Framework for Deriving Marketing Insights from the Texts of Consumers’ Consumption Stories , 1997 .

[20]  Susan Squires,et al.  Creating breakthrough ideas : the collaboration of anthropologists and designers in the product development industry , 2002 .

[21]  Nuno David,et al.  The Structure and Logic of Interdisciplinary Research in Agent-Based Social Simulation , 2004, J. Artif. Soc. Soc. Simul..

[22]  L. Izquierdo,et al.  The impact of quality uncertainty without asymmetric information on market efficiency , 2007 .

[23]  D. Morgan.  The Focus Group Guidebook , 1997 .

[24]  Bonnie Goebert,et al.  Beyond Listening: Learning the Secret Language of Focus Groups , 2001 .

[25]  Steven Durlauf.  Growing artificial societies , 1997, Complex..

[26]  Rosanna Garcia.  Uses of Agent-Based Modeling in Innovation/New Product Development Research , 2005 .

[27]  Elizabeth Chell,et al.  Critical incident technique. , 2003 .

[28]  簡聰富,et al.  物件導向軟體之架構(Object-Oriented Software Construction)探討 , 1989 .

[29]  László Gulyás,et al.  Sociodynamic Discrete Choice on Networks in Space: Impacts of Agent Heterogeneity on Emergent Outcomes , 2008 .

[30]  L. Johnston.  Template analysis. , 1987, Journal of clinical orthodontics : JCO.

[31]  Grounded Theory and Multi-Agent Simulation for a Small Firm , 2005 .

[32]  Hajime Kita,et al.  Agent-Based Simulation: From Modeling Methodologies to Real-World Applications , 2005 .

[33]  A. V. D. Ven,et al.  Longitudinal Field Research Methods for Studying Processes of Organizational Change , 1990 .

[34]  Andrew Abbott,et al.  A Primer on Sequence Methods , 1990 .

[35]  Nina Schwarz,et al.  Modelling of Water Use Decisions in a Large, Spacially Explicit, Coupled Simulation System , 2008 .

[36]  Lawrence B. Mohr,et al.  Conceptual issues in the study of innovation , 1976 .

[37]  J M Morse,et al.  Approaches to qualitative-quantitative methodological triangulation. , 1991, Nursing research.

[38]  Alison J. Heppenstall,et al.  Using Hybrid Agent-Based Systems to Model Spatially-Influenced Retail Markets , 2006, J. Artif. Soc. Soc. Simul..

[39]  Russell W. Belk,et al.  Videography in marketing and consumer research , 2005 .

[40]  Carlo C. DiClemente,et al.  The Transtheoretical Approach: Crossing Traditional Boundaries of Therapy , 1994 .

[41]  R. Yin.  Case Study Research: Design and Methods , 1984 .

[42]  Joshua M. Epstein,et al.  Growing Artificial Societies: Social Science from the Bottom Up , 1996 .

[43]  Alan D. Meyer,et al.  Visual Data in Organizational Research , 1991 .

[44]  A. Strauss,et al.  The discovery of grounded theory: strategies for qualitative research aldine de gruyter , 1968 .

[45]  T. S. Robertson,et al.  Handbook of Consumer Behavior , 1990 .

[46]  John W. Schouten,et al.  Brandfests: Servicescapes for the Cultivation of Brand Equity , 1998 .

[47]  A. Langley.  Strategies for Theorizing from Process Data , 1999 .

[48]  Guillaume Deffuant,et al.  Complexities in markets: Introduction to the special issue , 2007 .

[49]  A. Michael Huberman,et al.  An expanded sourcebook qualitative data analysis , 1994 .

[50]  Charles M. Weber,et al.  Opening the black box of technology adoption: The motive-technology-belief framework , 2009, PICMET '09 - 2009 Portland International Conference on Management of Engineering & Technology.

[51]  Susan Spiggle.  Analysis and Interpretation of Qualitative Data in Consumer Research , 1994 .

[52]  Anna De Fina,et al.  The ethnographic interview , 2019, The Routledge Handbook of Linguistic Ethnography.

[53]  N. Hoffart.  Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory , 2000 .

[54]  Eric J. Arnould,et al.  Deep Engagement With Consumer Experience: Listening and Learning With Qualitative Data , 2006 .

[55]  Brent A. Zenobia,et al.  Artificial markets: A review and assessment of a new venue for innovation research , 2009 .

[56]  G. Zaltman.  Rethinking Market Research: Putting People Back In , 1997 .

[57]  O. Svenson.  Decision Making and the Search for Fundamental Psychological Regularities: What Can Be Learned from a Process Perspective? , 1996 .

[58]  D L Morgan,et al.  Practical Strategies for Combining Qualitative and Quantitative Methods: Applications to Health Research , 1998, Qualitative health research.

[59]  Melanie Wallendorf,et al.  Market-Oriented Ethnography: Interpretation Building and Marketing Strategy Formulation , 1994 .

[60]  Lawrence B. Mohr,et al.  Explaining Organizational Behavior: The Limits and Possibilities of Theory and Research. , 1983 .

[61]  A. Langley,et al.  A PROCESS STUDY OF NEW TECHNOLOGY ADOPTION IN SMALLER MANUFACTURING FIRMS , 1994 .

[62]  Bertrand Meyer,et al.  Object-oriented software construction (2nd ed.) , 1997 .

[63]  Dorothy Leonard-Barton,et al.  A Dual Methodology for Case Studies: Synergistic Use of a Longitudinal Single Site with Replicated Multiple Sites , 1990 .

[64]  H. Bussell.  Qualitative Methods and Analysis in Organizational Research: A Practical Guide , 2000 .

[65]  Roberto Leombruni,et al.  A Common Protocol for Agent-Based Social Simulation , 2006, J. Artif. Soc. Soc. Simul..

[66]  Douglas Schuler,et al.  Participatory Design: Principles and Practices , 1993 .

[67]  G. Zaltman,et al.  Seeing the Voice of the Customer: Metaphor-based Advertising Research , 1995 .