Optimized Capacity Management Drives Financial Clusters Approach to Linear Programming

  • Mahdi Yami School of Business and Management, Donghua University, Shanghai, China
  • Changchun Gao School of Business and Management, Donghua University, Shanghai, China
Keywords: financial cluster, eco-industrial cluster, optimization Approach, linear programming, Earnings Impacts, decision-making

Abstract

This paper discusses methods for directly incorporating relationships in resource capacity optimization model. Developing a stable financial cluster needs the economic competitiveness in accumulation income of joint actions from all of the financial industry’s participants. To develop the competitiveness growth of the social capital capacity, discovering the new approaches to enhance the market assets is needed. The linear programming approach is one of the quantitative decision-making techniques to find the most efficient use of established business capacities management drives financial clusters. The case study of insurtech in Quebec of Canada and analyzes of the earning impact as criteria provided important insights on the system cost optimize can be located even while the number of clients and working time are limited. The market constraints are developed for optimum use of capacity on the basis of the clustering data of the local financial advisors and agents. According to the model, it is determined that a variety of problems using linear programming, which allows reliable solvability of even very large models, regarding the environmental factors into their decisions in financial industries.

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Published
2020-01-16
How to Cite
Yami, M., & Gao, C. (2020). Optimized Capacity Management Drives Financial Clusters Approach to Linear Programming. Journal of Research in Business, Economics and Management, 14(1), 2593-2600. Retrieved from http://scitecresearch.com/journals/index.php/jrbem/article/view/1826
Issue
Vol 14 No 1: JRBEM
Section
Articles

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