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Advanced Modeling: new methods and techniques for studying individual differences in organizations - EXTENDED DEADLINES


Advanced Modeling: new methods and techniques for studying individual differences in organizations

The SGM is anticipated by one day! Due to a concurrent event, the workshop will be held from Tuesday 13th to Thursday 15th September 2016.

Call for papers


Date: September 13-15, 2016

Location: Verona University, ITA

Main Organizer: Riccardo Sartori – Verona University

Conference Coordinator: Andrea Ceschi – Verona University


Scientific Committee: 

Stephan Dickert – Queen Mary University of London

Enrico Rubaltelli – Padova University 

Wander Jager – Groningen University

Margherita Pasini – Verona University

Natalie Van Der Wal - VU Amsterdam University


CONFERENCE THEME. Standard methods of investigation currently applied in Organizational Psychology do not guarantee the possibility of analyzing and predicting outcomes of the macroscopic structure, as well as the emergent properties of complex systems such as business organizations. In addition, any form of statistical analysis, even the most sophisticated, such as Structural Equation Models ignores the individual differences of the population. New research methods have been lately explored in recent years, starting from some solid scientific studies on individual behavior and using advance computing techniques capable of “growing up" phenomena at the macro level, making it possible to obtain counterintuitive findings about behavior and implications in organizations. This approach additionally permits one to experiment with parameters such as individual’s rationality, something which is difficult to address with a purely statistical approach. The present special issue aims to propose a series of contribution for Organizational Studies not purely simulation based, but a hybrid between the classical static and statistical model approach, and the dynamic modelling.

Indeed, a promising area of application of ABMs and of Growth Mixture Models are organizations, where it is possible to model social behaviors to investigate organizational outcomes (Smith & Conrey, 2007). Knowing for example the potential antecedes connected to some social-behavior, such as counterproductive behaviors (Interpersonal deviance, Abusive supervision, etc.), as well behaviors oriented to positive values (such as Teamwork, Career choices, etc.), it is possible to recreate the same phenomena using computer simulation for predictive purposes (Fioretti, 2013; Hughes, Clegg, Robinson, & Crowder, 2012; Sartori, Ceschi, & Scalco, 2014; Weinhardt & Vancouver, 2012). 

METHODOLOGY. These methods are not presented as strict substitutes of the traditional statistical analysis, but as an extension of it, in order to obtain results capable of explaining more variance. The aim of this new approach allows a direct comparison of ABM with standard statistical methodologies, especially SEM based, whilst retaining the potential advantages of ABM and of Growth Mixture Models.

NATURE OF THE CONFERENCE. The present conference cycle aims to propose a new approach for Organizational Studies, a hybrid between the classical statistical model approach, and the dynamic modeling. These methods are not presented as strict substitutes of the traditional statistical analyses, but as an extension of it, in order to obtain results capable of explaining more variance in the situations analyzed. The aim is develop a new approach which allow a direct comparison of Agent Based Model (ABM) and Growth Mixture Models (GMM) with standard statistical methodologies, Structural Equation Model (SEM) based, whilst retaining the potential advantages of these new methods. The Small Group Meeting is a workshop of three days. We intend to create a productive conference-meeting group to introduce ABM and Growth Mixture Models, and to exchange approaches, methods and critics aiming to improve the methodology of research. The conference will focus on the methodology and instruments, by proposing exercises and the application of the methods proposed.

MEETING LOCATION AND RESIDENCE. The small meeting will be held in the Department of Human Sciences of the Verona University. In this campus we also have an international university residence very convenient for this event. For information about accommodation, please write to

SUBMISSION OF ABSTRACTS. An abstract based on the provided guidelines (up to 300 words) should be submitted by 31st May 2016 to (please, specify the email object like this “Submission VERONASGM2016”). Each contribution will be evaluated at least by 2 peer reviewers, according to the relevance to the SGM topics, significance of the contribution, and originality. Submissions should be structured as follows: purpose of the contribution, design/methodology, results, limitations, conclusion/implications. Please, also describe the originality of your contribution. Participants will be notified regarding the acceptance of their paper by June 15, 2016.

FULL PAPERS AND GUIDELINES. Full papers should be submitted by the 30th September 2016. Full papers should be comprised between 4.000 and 6.000 words (including list of references, figures, and tables). Figures and tables can be embedded in the text. The first page, on which the paper body begins, should include the title, authors (including affiliation and contact email of each author), abstract (up to 150 words), and keywords (up to six). Citation style must be formatted according to the APA style 6th edition (for more information, please visit ).

PUBLICATION OF PAPERS. Accepted papers will be published on a Special Issue of Mind&Society (Springer journal). More information about the Special Issue guidelines for submission will be provided to selected papers at the workshop.

REGISTRATION. For the contribution to be qualified as oral presentation during the SGM and to be selected as paper to be published inside the Special Issue, it is required that at least one of the authors will confirm the participation to the meeting. No registration fee is required

MORE INFORMATION. To receive more information and remain updated about the conference, please visit the official site of the SGM: For any further information, please do not hesitate to contact R. Sartori (


Epstein, J. M. (2009). Modelling to contain pandemics. Nature, 460(7256), 687-687. 

Farmer, J. D., & Foley, D. (2009). The economy needs agent-based modelling. Nature, 460(7256), 685-686. 

Fioretti, G. (2013). Agent-based simulation models in organization science. Organizational Research Methods, 16(2), 227-242. 

Hughes, H. P., Clegg, C. W., Robinson, M. A., & Crowder, R. M. (2012). Agent?based modelling and simulation: The potential contribution to organizational psychology. Journal of Occupational and Organizational Psychology, 85(3), 487-502. 

Richetin, J., Sengupta, A., Perugini, M., Adjali, I., Hurling, R., Greetham, D., & Spence, M. (2010). A micro-level simulation for the prediction of intention and behavior. Cognitive Systems Research, 11(2), 181-193. 

Sartori, R., Ceschi, A., & Scalco, A. (2014). Differences between Entrepreneurs and Managers in Large Organizations: An Implementation of a Theoretical Multi-Agent Model on Overconfidence Results Distributed Computing and Artificial Intelligence, 11th International Conference (pp. 79-83): Springer.

Smith, E. R., & Conrey, F. R. (2007). Agent-based modeling: A new approach for theory building in social psychology. Personality and social psychology review, 11(1), 87-104. 

Weinhardt, J. M., & Vancouver, J. B. (2012). Computational models and organizational psychology: Opportunities abound. Organizational Psychology Review, 2(4), 267-292.