Abstract
The success or failure of software development group work depends on the group members’ personalities, as well as their skills in performing various tasks associated with the project. Moreover, in the reality, tasks have a dynamic nature and their requirements change over time. Therefore, the effect of task dynamics on the teamwork must be taken into consideration. To do so, after describing a general approach to select effective team members based on their personalities and skills, we consider as an example a comparative multi-agent simulation study contrasting two different sample strategies that managers could use to select team members: by minimizing team over-competency and by minimizing team under-competency. Based on the simulation results, we drive a set of propositions about the conditions under which there are and are not performance benefits from employing a particular strategy for task allocation. Also, we propose a simulation environment that could provide a low cost tool for managers and researchers to gain better insights about effectiveness of different task allocation strategies and employees with different attributes in dynamic environments.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
André, M., Baldoquín, M.G., Acuña, S.T.: Formal model for assigning human resources to teams in software projects. Inf. Softw. Technol. 53(3), 259–275 (2011)
LePine, J.A., Buckman, B.R., Crawford, E.R., Methot, J.R.: A review of research on personality in teams: accounting for pathways spanning levels of theory and analysis. Hum. Resour. Manage. Rev. 21(4), 311–330 (2011)
Wood, R.E.: Task complexity: definition of the construct. Organ. Behav. Hum. Decis. Process. 37(1), 60–82 (1986)
Zoethout, K., Jager, W., Molleman, E.: Task dynamics in self-organising task groups: expertise, motivational, and performance differences of specialists and generalists. Auton. Agent. Multi. Agent. Syst. 16(1), 75–94 (2007)
Jiang, G., Hu, B., Wang, Y.: Agent-based simulation approach to understanding the interaction between employee behavior and dynamic tasks. Simulation 87(5), 407–422 (2010)
Acuña, S.T., Gómez, M., Juristo, N.: How do personality, team processes and task characteristics relate to job satisfaction and software quality? Inf. Softw. Technol. 51(3), 627–639 (2009)
Myers, I.B., McCaulley, M.H.: Manual: a Guide to the Development and Use of the Myers-Briggs Type Indicator. Consulting Psychologists Press (1985)
Belbin, R.M.: Team Roles at Work. Routledge, London (2012)
Myers, I.: The Myers-Briggs Type Indicator. Consulting Psychologists Press (1962)
Jung, C.G.: Psychological Types: or the Psychology of Individuation. Harcourt, Brace (1921)
Belbin, R.M.: Management Teams: Why they Succeed or Fail. Bulletin of the British Psychological Society (1981)
Stevens, K.T.: The effects of roles and personality characteristics on software development team effectiveness. Dissertation, Virginia Polytechnic Institute and State University (1998)
Henry, S.M., Todd Stevens, K.: Using Belbin’s leadership role to improve team effectiveness: an empirical investigation. J. Syst. Softw. 44(3), 241–250 (1999)
Stevens, K., Henry, S.: Analysing software teams using Belbin’s innovative plant role. Department of Computer and Information Science, University of Mississippi and Department of Computer Science, Virginia Tech (2002)
Schoenhoff, P.K.: Belbin’s Company Worker, The Self-Perception Inventory, and Their Application to Software Engineering Teams. Dissertation, Virginia Polytechnic Institute and State University (2001)
Myers, S.: MTR-i: a new arena for team roles. Training JOURNAL-ELY- 24–29 (2002)
Keirsey, D.: Please understand me II: temperament, character, intelligence. Prometheus Nemesis (Del Mar, CA), p. 350 (1998)
Higgs, M.J.: A comparison of Myers Briggs type indicator profiles and Belbin team roles. Henley Business School, University of Reading, 21 Aug 1996
Chen, S.-J.G.: An integrated methodological framework for project task coordination and team organization in concurrent engineering. Concurr. Eng. 185–197 (2005)
Bayne, R.: The Myers-Briggs Type Indicator: a Critical Review and Practical Guide (1995)
Bradley, J.H., Hebert, F.J.: The effect of personality type on team performance. J. Manage. Dev. 16(5), 337–353 (1997)
Culp, G., Smith, A.: Understanding psychological type to improve project team performance. J. Manage. Eng. 17(1), 24–33 (2001)
Varvel, T., Adams, S.G., Pridie, S.J., Ruiz Ulloa, B.C.: Team effectiveness and individual Myers-Briggs personality dimensions. J. Manage. Eng. 20(4), 141–146 (2004)
Bowers, C.A., Pharmer, J.A., Salas, E.: When member homogeneity is needed in work teams: a meta-analysis. Small Group Res. 31(3), 305–327 (2000)
Canos, L., Liern, V.: Some fuzzy models for human resource management. Int. J. Technol. Policy Manage. 291–308 (2004)
Tisue, S., Wilensky, U.: NetLogo: design and implementation of a multi-agent modeling environment. In: Proceedings of Agent (2004)
Vargha, A., Delaney, H.D.: A critique and improvement of the cl common language effect size statistics of McGraw and Wong. J. Educ. Behav. Stat. 25(2), 101–132 (2000)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Farhangian, M., Purvis, M., Purvis, M., Savarimuthu, T.B.R. (2015). Agent-Based Modeling of Resource Allocation in Software Projects Based on Personality and Skill. In: Koch, F., Guttmann, C., Busquets, D. (eds) Advances in Social Computing and Multiagent Systems. MFSC 2015. Communications in Computer and Information Science, vol 541. Springer, Cham. https://doi.org/10.1007/978-3-319-24804-2_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-24804-2_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24803-5
Online ISBN: 978-3-319-24804-2
eBook Packages: Computer ScienceComputer Science (R0)