Advances in Economics, Management and Political Sciences

- The Open Access Proceedings Series for Conferences


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

Series Vol. 32 , 10 November 2023


Open Access | Article

Consumer and Marketing Research Using the Monte Carlo Simulation

Xiangyuan Huang * 1
1 Guanghua Cambridge International School

* Author to whom correspondence should be addressed.

Advances in Economics, Management and Political Sciences, Vol. 32, 35-41
Published 10 November 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Xiangyuan Huang. Consumer and Marketing Research Using the Monte Carlo Simulation. AEMPS (2023) Vol. 32: 35-41. DOI: 10.54254/2754-1169/32/20231561.

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

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.

Data Availability

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

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).

Volume Title
Proceedings of the 7th International Conference on Economic Management and Green Development
ISBN (Print)
978-1-83558-085-1
ISBN (Online)
978-1-83558-086-8
Published Date
10 November 2023
Series
Advances in Economics, Management and Political Sciences
ISSN (Print)
2754-1169
ISSN (Online)
2754-1177
DOI
10.54254/2754-1169/32/20231561
Copyright
10 November 2023
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated