Large-Scale Agent-Based Models in Marketing Research: The Quest for the Mythical Free Lunch

Alexandru Voicu; Cristina Galalae

doi:doi:10.11648/j.ijber.20130203.11

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Large-Scale Agent-Based Models in Marketing Research: The Quest for the Mythical Free Lunch

Alexandru Voicu, Cristina Galalae

Published in International Journal of Business and Economics Research (Volume 2, Issue 3)

Received: 20 May 2013 Published: 10 June 2013

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Abstract

Positioned as an alternative to equation-based methods, agent-based modelling (ABM) has shown notable promise in dealing with cases where the latter has proven inadequate. One of the areas where the limitations of traditional approaches are most pronounced is that of consumer behaviour research. A primary trait encountered within this scope is that of adaptability, and agent-based methods appear to be ideally suited to the task of capturing this dimension. It therefore follows that marketing researchers are likely to gain novel and extensive insight by way of constructing large-scale, complex ABMs. However, the computational cost of complex simulations can be prohibitive. Furthermore, the literature makes little effort to elucidate means of making such ABMs feasible, beyond relying on natural hardware evolution. Unfortunately, the latter source of growth has grown stagnant, and the only avenue for the continued expansion of performance appears to be the move to parallel platforms and programming. The present research presents a cross-section of the current state-of-the-art in high-performance ABM frameworks, and proposes a novel approach to levering the as of yet untapped potential of cheap, ubiquitous Graphics Processing Units (GPUs). This insight is mapped into the space of consumer behaviour research, and a consistent argument is made in favour of larger, more detailed, ABMs, both as alternatives to current approaches as well as a development of prior forays into this area. In conclusion, a call to action is formulated, both to marketing researchers as well as computational economists, emphasizing the interdisciplinary requirements of ABM usage in the field of marketing.

Published in	International Journal of Business and Economics Research (Volume 2, Issue 3)
DOI	10.11648/j.ijber.20130203.11
Page(s)	33-40
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2013. Published by Science Publishing Group

Keywords

Agent-Based Modelling, Consumer Behaviour, Parallel Programming, GPGPU, C++ AMP, Economics

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Alexandru Voicu, Cristina Galalae. (2013). Large-Scale Agent-Based Models in Marketing Research: The Quest for the Mythical Free Lunch. International Journal of Business and Economics Research, 2(3), 33-40. https://doi.org/10.11648/j.ijber.20130203.11

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ACS Style

Alexandru Voicu; Cristina Galalae. Large-Scale Agent-Based Models in Marketing Research: The Quest for the Mythical Free Lunch. Int. J. Bus. Econ. Res. 2013, 2(3), 33-40. doi: 10.11648/j.ijber.20130203.11

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AMA Style

Alexandru Voicu, Cristina Galalae. Large-Scale Agent-Based Models in Marketing Research: The Quest for the Mythical Free Lunch. Int J Bus Econ Res. 2013;2(3):33-40. doi: 10.11648/j.ijber.20130203.11

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@article{10.11648/j.ijber.20130203.11,
  author = {Alexandru Voicu and Cristina Galalae},
  title = {Large-Scale Agent-Based Models in Marketing Research: The Quest for the Mythical Free Lunch},
  journal = {International Journal of Business and Economics Research},
  volume = {2},
  number = {3},
  pages = {33-40},
  doi = {10.11648/j.ijber.20130203.11},
  url = {https://doi.org/10.11648/j.ijber.20130203.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20130203.11},
  abstract = {Positioned as an alternative to equation-based methods, agent-based modelling (ABM) has shown notable promise in dealing with cases where the latter has proven inadequate. One of the areas where the limitations of traditional approaches are most pronounced is that of consumer behaviour research. A primary trait encountered within this scope is that of adaptability, and agent-based methods appear to be ideally suited to the task of capturing this dimension. It therefore follows that marketing researchers are likely to gain novel and extensive insight by way of constructing large-scale, complex ABMs. However, the computational cost of complex simulations can be prohibitive. Furthermore, the literature makes little effort to elucidate means of making such ABMs feasible, beyond relying on natural hardware evolution. Unfortunately, the latter source of growth has grown stagnant, and the only avenue for the continued expansion of performance appears to be the move to parallel platforms and programming. The present research presents a cross-section of the current state-of-the-art in high-performance ABM frameworks, and proposes a novel approach to levering the as of yet untapped potential of cheap, ubiquitous Graphics Processing Units (GPUs). This insight is mapped into the space of consumer behaviour research, and a consistent argument is made in favour of larger, more detailed, ABMs, both as alternatives to current approaches as well as a development of prior forays into this area. In conclusion, a call to action is formulated, both to marketing researchers as well as computational economists, emphasizing the interdisciplinary requirements of ABM usage in the field of marketing.},
 year = {2013}
}

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TY  - JOUR
T1  - Large-Scale Agent-Based Models in Marketing Research: The Quest for the Mythical Free Lunch
AU  - Alexandru Voicu
AU  - Cristina Galalae
Y1  - 2013/06/10
PY  - 2013
N1  - https://doi.org/10.11648/j.ijber.20130203.11
DO  - 10.11648/j.ijber.20130203.11
T2  - International Journal of Business and Economics Research
JF  - International Journal of Business and Economics Research
JO  - International Journal of Business and Economics Research
SP  - 33
EP  - 40
PB  - Science Publishing Group
SN  - 2328-756X
UR  - https://doi.org/10.11648/j.ijber.20130203.11
AB  - Positioned as an alternative to equation-based methods, agent-based modelling (ABM) has shown notable promise in dealing with cases where the latter has proven inadequate. One of the areas where the limitations of traditional approaches are most pronounced is that of consumer behaviour research. A primary trait encountered within this scope is that of adaptability, and agent-based methods appear to be ideally suited to the task of capturing this dimension. It therefore follows that marketing researchers are likely to gain novel and extensive insight by way of constructing large-scale, complex ABMs. However, the computational cost of complex simulations can be prohibitive. Furthermore, the literature makes little effort to elucidate means of making such ABMs feasible, beyond relying on natural hardware evolution. Unfortunately, the latter source of growth has grown stagnant, and the only avenue for the continued expansion of performance appears to be the move to parallel platforms and programming. The present research presents a cross-section of the current state-of-the-art in high-performance ABM frameworks, and proposes a novel approach to levering the as of yet untapped potential of cheap, ubiquitous Graphics Processing Units (GPUs). This insight is mapped into the space of consumer behaviour research, and a consistent argument is made in favour of larger, more detailed, ABMs, both as alternatives to current approaches as well as a development of prior forays into this area. In conclusion, a call to action is formulated, both to marketing researchers as well as computational economists, emphasizing the interdisciplinary requirements of ABM usage in the field of marketing.
VL  - 2
IS  - 3
ER  -

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Author Information

Alexandru Voicu

Faculty of Management, Bucharest Academy of Economic Studies, Bucharest, Romania
Cristina Galalae

Faculty of Economics and International Business, Bucharest Academy of Economic Studies, Bucharest, Romania

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APA Style

Alexandru Voicu, Cristina Galalae. (2013). Large-Scale Agent-Based Models in Marketing Research: The Quest for the Mythical Free Lunch. International Journal of Business and Economics Research, 2(3), 33-40. https://doi.org/10.11648/j.ijber.20130203.11

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ACS Style

Alexandru Voicu; Cristina Galalae. Large-Scale Agent-Based Models in Marketing Research: The Quest for the Mythical Free Lunch. Int. J. Bus. Econ. Res. 2013, 2(3), 33-40. doi: 10.11648/j.ijber.20130203.11

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AMA Style

Alexandru Voicu, Cristina Galalae. Large-Scale Agent-Based Models in Marketing Research: The Quest for the Mythical Free Lunch. Int J Bus Econ Res. 2013;2(3):33-40. doi: 10.11648/j.ijber.20130203.11

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@article{10.11648/j.ijber.20130203.11,
  author = {Alexandru Voicu and Cristina Galalae},
  title = {Large-Scale Agent-Based Models in Marketing Research: The Quest for the Mythical Free Lunch},
  journal = {International Journal of Business and Economics Research},
  volume = {2},
  number = {3},
  pages = {33-40},
  doi = {10.11648/j.ijber.20130203.11},
  url = {https://doi.org/10.11648/j.ijber.20130203.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20130203.11},
  abstract = {Positioned as an alternative to equation-based methods, agent-based modelling (ABM) has shown notable promise in dealing with cases where the latter has proven inadequate. One of the areas where the limitations of traditional approaches are most pronounced is that of consumer behaviour research. A primary trait encountered within this scope is that of adaptability, and agent-based methods appear to be ideally suited to the task of capturing this dimension. It therefore follows that marketing researchers are likely to gain novel and extensive insight by way of constructing large-scale, complex ABMs. However, the computational cost of complex simulations can be prohibitive. Furthermore, the literature makes little effort to elucidate means of making such ABMs feasible, beyond relying on natural hardware evolution. Unfortunately, the latter source of growth has grown stagnant, and the only avenue for the continued expansion of performance appears to be the move to parallel platforms and programming. The present research presents a cross-section of the current state-of-the-art in high-performance ABM frameworks, and proposes a novel approach to levering the as of yet untapped potential of cheap, ubiquitous Graphics Processing Units (GPUs). This insight is mapped into the space of consumer behaviour research, and a consistent argument is made in favour of larger, more detailed, ABMs, both as alternatives to current approaches as well as a development of prior forays into this area. In conclusion, a call to action is formulated, both to marketing researchers as well as computational economists, emphasizing the interdisciplinary requirements of ABM usage in the field of marketing.},
 year = {2013}
}

Copy | Download

TY  - JOUR
T1  - Large-Scale Agent-Based Models in Marketing Research: The Quest for the Mythical Free Lunch
AU  - Alexandru Voicu
AU  - Cristina Galalae
Y1  - 2013/06/10
PY  - 2013
N1  - https://doi.org/10.11648/j.ijber.20130203.11
DO  - 10.11648/j.ijber.20130203.11
T2  - International Journal of Business and Economics Research
JF  - International Journal of Business and Economics Research
JO  - International Journal of Business and Economics Research
SP  - 33
EP  - 40
PB  - Science Publishing Group
SN  - 2328-756X
UR  - https://doi.org/10.11648/j.ijber.20130203.11
AB  - Positioned as an alternative to equation-based methods, agent-based modelling (ABM) has shown notable promise in dealing with cases where the latter has proven inadequate. One of the areas where the limitations of traditional approaches are most pronounced is that of consumer behaviour research. A primary trait encountered within this scope is that of adaptability, and agent-based methods appear to be ideally suited to the task of capturing this dimension. It therefore follows that marketing researchers are likely to gain novel and extensive insight by way of constructing large-scale, complex ABMs. However, the computational cost of complex simulations can be prohibitive. Furthermore, the literature makes little effort to elucidate means of making such ABMs feasible, beyond relying on natural hardware evolution. Unfortunately, the latter source of growth has grown stagnant, and the only avenue for the continued expansion of performance appears to be the move to parallel platforms and programming. The present research presents a cross-section of the current state-of-the-art in high-performance ABM frameworks, and proposes a novel approach to levering the as of yet untapped potential of cheap, ubiquitous Graphics Processing Units (GPUs). This insight is mapped into the space of consumer behaviour research, and a consistent argument is made in favour of larger, more detailed, ABMs, both as alternatives to current approaches as well as a development of prior forays into this area. In conclusion, a call to action is formulated, both to marketing researchers as well as computational economists, emphasizing the interdisciplinary requirements of ABM usage in the field of marketing.
VL  - 2
IS  - 3
ER  -

Copy | Download