Abstract

According to the previous research, proper demand forecasting could help construction-related firms in effective planning for future market changes. However, existing market demand forecasting models are somewhat limited, and most of them bear some critical shortcomings. This research aims to develop a forecasting model for the Korean residential construction industry using system dynamics. In developing the market forecasting model, this research uses variables that significantly impact future construction market change. Many of the existing models do not include as many variables as this model, and none of them have considered complex interlocking effects among these variables. This model is also the first model using a system-based approach by looking at the target industry as a ‘one complex system’ rather than focusing on individual variables’ impact on future market changes. By employing system dynamics, it is possible to consider qualitative and quantitative aspects and produce long-term market forecasting results. The developed market forecasting model consists of two main modules, the first being a prediction module for the grassroots construction market and the second for operation and maintenance (O&M) and the demolition market. Sixteen input variables are grouped into four categories: social, economy, regulation, and past market size among over 25 identified variables. The model utilizes a mathematical function system using the designed feedback loops in producing future market forecasts. Based on the validation tests with past market data, it turns out that the model is reliable, with the determination coefficient (R2) being over 0.7 on all tested occasions. According to the model’s forecasting results, the Korean construction market’s size is expected to be 231 billion won in 2015 and 286 billion won in 2030. However, the O&M market’s growth rate is expected to be higher than 180%, which is much bigger than those of the grass-root and demolition markets. Thus, this research model is realistic according to the construction paradigm change. This research is considered one of the pioneering studies in construction market forecasting by employing dynamic inter-relationships among various input variables. Therefore, the market forecasting results can be interpreted as more practical and can provide more insights to the construction industry stakeholders. The model is envisioned to provide the public sector with useful guidelines in preparing future public market supply strategies such as construction budget allocations. It would also be helpful for the private sector to develop more proactive and accurate demand strategies for timely decision-making.

Highlights

  • This study develops a model to forecast the size of demand in the construction market based on a systematic approach

  • Write a simulation model that hinders the activation of the Construction Management (CM) market and suggest ways to improve each risk factor

  • Development of System Dynamics (SD) model based on primary factors that make up the residential market and the impact of the government’s deregulation on mortgage market participants

Read more

Summary

Introduction

Since the construction industry mainly deals with closed offline transactions, access to information on companies and prices is very low. These problems cause a negative perception of society in the construction industry. The construction industry needs to change the demand structure by securing transactions’ accessibility and transparency by changing the offline-oriented market to online-centered like other industries, it is necessary to analyze the industry’s size, the existing demand environment, and future demand accurately to transform the demand structure. Demand forecasting can promote the industry’s revitalization by creating a new business model for suppliers by establishing a proactive response strategy according to future demand changes

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call