Consumer and Marketing Research Using the Monte Carlo Simulation

Research Article
Open access

Consumer and Marketing Research Using the Monte Carlo Simulation

Xiangyuan Huang 1*
  • 1 Guanghua Cambridge International School    
  • *corresponding author 31240015@caa.edu.cn
Published on 10 November 2023 | https://doi.org/10.54254/2754-1169/32/20231561
AEMPS Vol.32
ISSN (Print): 2754-1177
ISSN (Online): 2754-1169
ISBN (Print): 978-1-83558-085-1
ISBN (Online): 978-1-83558-086-8

Abstract

In order to conduct consumer-related research and develop marketing strategies to outperform rival businesses, Monte Carlo simulation, a technique that was first employed in nuclear weapons and has subsequently been used in other physics-related domains, is described in this study. The literature on using Monte Carlo simulation for market and customer-related research and suggestions is summarized in two parts in this paper. The first section discusses the role of Monte Carlo simulations in customer research, outlining the various factors that affect consumers' decisions to purchase goods and services, and the second section discusses the specific help that Monte Carlo simulations can offer businesses, particularly in terms of measuring markets and creating effective marketing strategies. The paper also offers several applicable examples to describe certain elements in the middle of the text. Eventually, it is argued that Monte Carlo simulation, when used in conjunction with other techniques, can assist businesses in comprehending the market's costs and unpredictability and in developing effective marketing strategies.

Keywords:

Mente Carlo simulation, marketing, customer research, marketing strategies

Huang,X. (2023). Consumer and Marketing Research Using the Monte Carlo Simulation. Advances in Economics, Management and Political Sciences,32,35-41.
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References

[1]. Parvatiyar, A., & Sheth, J. N. (2001). Customer relationship management: Emerging practice, process, and discipline. Journal of Economic and Social Research, 1–34.

[2]. Furness P. Applications of Monte Carlo Simulation in marketing analytics[J]. Journal of Direct, Data and Digital Marketing Practice, 2011, 13: 132-147.

[3]. Taylor, M., Kwasnica, V., Reilly, D. and Ravindran, S. (2019), "Game theory modelling of retail marketing discount strategies", Marketing Intelligence & Planning, Vol. 37 No. 5, pp. 555-566.

[4]. Prayag, Hassibi, & Nunkoo. (2019). A systematic review of consumer satisfaction studies in hospitality journals: conceptual development, research approaches and future prospects. Journal of Hospitality Marketing & 38 Management.

[5]. Jaemin, C. , & Borchgrevink, C. P. . (2018). Customers' perceptions in value and food safety on customer satisfaction and loyalty in restaurant environments: moderating roles of gender and restaurant types. Journal of Quality Assurance in Hospitality & Tourism, 1-19.

[6]. Daulay, R., & Saputra, R. (2019). Analysis of Customer Relationship Management and Marketing Strategies Against Competitive Advantage on the company's distributor in Medan City. Proceedings of the Proceedings of the 1st International Conference on Economics, Management, Accounting and Business, ICEMAB 2018, 8-9 October 2018, Medan, North Sumatra, Indonesia.

[7]. Lie, D. , Sudirman, A. , Butarbutar, M. , & Efendi, E. . (2019). Analysis of mediation effect of consumer satisfaction on the effect of service quality, price and consumer trust on consumer loyalty. International Journal of Scientific & Technology Research.

[8]. Chun Y H. Monte Carlo analysis of estimation methods for the prediction of customer response patterns in direct marketing[J]. European Journal of Operational Research, 2012, 217(3): 673-678.

[9]. Gao, Y. L. , Zhang, L. , & Wei, W. . (2021). The effect of perceived error stability, brand perception, and relationship norms on consumer reaction to data breaches. International Journal of Hospitality Management, 94(1), 102802.

[10]. Pengyi, S., & Xiucheng, F. (2016). Online Retail Enterprises' Social Responsibility Behavior and Consumer Response:A Moderating Model in the Chinese Context. China Soft Science(3), 11.

[11]. Alamsyah, A. , & Nurriz, B. . (2017). Monte carlo simulation and clustering for customer segmentation in business organization. IEEE, 104-109.

[12]. Akar, E. . Customers' online purchase intentions and customer segmentation during the period of covid-19 pandemic. Journal of Internet Commerce.

[13]. Goel, L. , Liang, X. , & Ou, Y. . (1999). Monte carlo simulation-based customer service reliability assessment. Electric Power Systems Research, 49(3), 185–194.

[14]. Savchenko, A. Y. . (2017). THE GREAT IMPORTANCE OF HUMAN REACTION IN MARKETING.

[15]. Cano J, Campo E, Gómez-Montoya R. International market selection using fuzzy weighing and Monte Carlo simulation[J]. Polish Journal of Management Studies, 2017, 16(2): 40-50.

[16]. Zhu B, Yu L A, Geng Z Q. Cost estimation method based on parallel Monte Carlo simulation and market investigation for engineering construction project[J]. Cluster Computing, 2016, 19: 1293-1308.

[17]. Li, T., Shahidehpour, M., & Li, Z. (2007). Risk-constrained bidding strategy with Stochastic Unit Commitment. IEEE Transactions on Power Systems, 22(1), 449–458.

[18]. Shi T, Liu X, Li J. Market segmentation by travel motivations under a transforming economy: Evidence from the Monte Carlo of the Orient[J]. Sustainability, 2018, 10(10): 3395.

[19]. Echdar, S. (2013). Entrepreneurship Management: Tips for Being an Entrepreneur. Yogyakarta: ANDI Publisher

[20]. Legoherel, P. (1998). Toward a market segmentation of the tourism trade: Journal of Travel & Tourism Marketing, 7(3), 19–39.

[21]. Korpioja , E.-M. (2022). From Data to Insight: Monte Carlo Simulation as a Marketing Intelligence Tool . From Data to Insight: Monte Carlo Simulation as a Marketing Intelligence Tool.

[22]. Morgan, N. A., Whitler, K. A., Feng, H., & Chari, S. (2018). Research in marketing strategy. Journal of the Academy of Marketing Science, 47(1), 4–29.

Cite this article

Huang,X. (2023). Consumer and Marketing Research Using the Monte Carlo Simulation. Advances in Economics, Management and Political Sciences,32,35-41.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 7th International Conference on Economic Management and Green Development

ISBN：978-1-83558-085-1(Print) / 978-1-83558-086-8(Online)
Editor：Canh Thien Dang
Conference website: https://www.icemgd.org/
Conference date: 6 August 2023
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.32
ISSN：2754-1169(Print) / 2754-1177(Online)

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References

[1]. Parvatiyar, A., & Sheth, J. N. (2001). Customer relationship management: Emerging practice, process, and discipline. Journal of Economic and Social Research, 1–34.

[2]. Furness P. Applications of Monte Carlo Simulation in marketing analytics[J]. Journal of Direct, Data and Digital Marketing Practice, 2011, 13: 132-147.

[3]. Taylor, M., Kwasnica, V., Reilly, D. and Ravindran, S. (2019), "Game theory modelling of retail marketing discount strategies", Marketing Intelligence & Planning, Vol. 37 No. 5, pp. 555-566.

[4]. Prayag, Hassibi, & Nunkoo. (2019). A systematic review of consumer satisfaction studies in hospitality journals: conceptual development, research approaches and future prospects. Journal of Hospitality Marketing & 38 Management.

[5]. Jaemin, C. , & Borchgrevink, C. P. . (2018). Customers' perceptions in value and food safety on customer satisfaction and loyalty in restaurant environments: moderating roles of gender and restaurant types. Journal of Quality Assurance in Hospitality & Tourism, 1-19.

[6]. Daulay, R., & Saputra, R. (2019). Analysis of Customer Relationship Management and Marketing Strategies Against Competitive Advantage on the company's distributor in Medan City. Proceedings of the Proceedings of the 1st International Conference on Economics, Management, Accounting and Business, ICEMAB 2018, 8-9 October 2018, Medan, North Sumatra, Indonesia.

[7]. Lie, D. , Sudirman, A. , Butarbutar, M. , & Efendi, E. . (2019). Analysis of mediation effect of consumer satisfaction on the effect of service quality, price and consumer trust on consumer loyalty. International Journal of Scientific & Technology Research.

[8]. Chun Y H. Monte Carlo analysis of estimation methods for the prediction of customer response patterns in direct marketing[J]. European Journal of Operational Research, 2012, 217(3): 673-678.

[9]. Gao, Y. L. , Zhang, L. , & Wei, W. . (2021). The effect of perceived error stability, brand perception, and relationship norms on consumer reaction to data breaches. International Journal of Hospitality Management, 94(1), 102802.

[10]. Pengyi, S., & Xiucheng, F. (2016). Online Retail Enterprises' Social Responsibility Behavior and Consumer Response:A Moderating Model in the Chinese Context. China Soft Science(3), 11.

[11]. Alamsyah, A. , & Nurriz, B. . (2017). Monte carlo simulation and clustering for customer segmentation in business organization. IEEE, 104-109.

[12]. Akar, E. . Customers' online purchase intentions and customer segmentation during the period of covid-19 pandemic. Journal of Internet Commerce.

[13]. Goel, L. , Liang, X. , & Ou, Y. . (1999). Monte carlo simulation-based customer service reliability assessment. Electric Power Systems Research, 49(3), 185–194.

[14]. Savchenko, A. Y. . (2017). THE GREAT IMPORTANCE OF HUMAN REACTION IN MARKETING.

[15]. Cano J, Campo E, Gómez-Montoya R. International market selection using fuzzy weighing and Monte Carlo simulation[J]. Polish Journal of Management Studies, 2017, 16(2): 40-50.

[16]. Zhu B, Yu L A, Geng Z Q. Cost estimation method based on parallel Monte Carlo simulation and market investigation for engineering construction project[J]. Cluster Computing, 2016, 19: 1293-1308.

[17]. Li, T., Shahidehpour, M., & Li, Z. (2007). Risk-constrained bidding strategy with Stochastic Unit Commitment. IEEE Transactions on Power Systems, 22(1), 449–458.

[18]. Shi T, Liu X, Li J. Market segmentation by travel motivations under a transforming economy: Evidence from the Monte Carlo of the Orient[J]. Sustainability, 2018, 10(10): 3395.

[19]. Echdar, S. (2013). Entrepreneurship Management: Tips for Being an Entrepreneur. Yogyakarta: ANDI Publisher

[20]. Legoherel, P. (1998). Toward a market segmentation of the tourism trade: Journal of Travel & Tourism Marketing, 7(3), 19–39.

[21]. Korpioja , E.-M. (2022). From Data to Insight: Monte Carlo Simulation as a Marketing Intelligence Tool . From Data to Insight: Monte Carlo Simulation as a Marketing Intelligence Tool.

[22]. Morgan, N. A., Whitler, K. A., Feng, H., & Chari, S. (2018). Research in marketing strategy. Journal of the Academy of Marketing Science, 47(1), 4–29.

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