A dynamic model of profit of residential projects in Vietnam

It is difficult to estimate the profit of residential projects as there are a number of complicated relationships among key profit factors. This study develops a dynamic model of the profit of residential projects in Ho Chi Minh City, Vietnam, utilizing a system dynamic approach, to examine the profit of residential projects in the long term. Five key profit factors, including the Urban Population, Buyer Capacity, Housing Supply, Housing Economics, and Housing Finance factors, are used to develop the dynamic model. Simulation results reveal that the average profit of residential projects in Ho Chi Minh City, Vietnam, in the next 20 years, is 35%, with a minimum and maximum profit of 19% and 41%, respectively. Scenario analyses recommend that a 30% down payment, a 25-year payment period, and a debt to equity ratio of 40% are the best strategies that residential companies should use to maximize profit in the long term. It is also recommended that debt to equity ratio and house price should be maintained in the early years to assist low-income households. The developed model can be used as a starting point to develop a software that allows developers to examine strategies by simply inputting their available data

Reverse logistics implementation in the construction industry: Paper waste focus

Thailand has an increasing demand for housing and infrastructure. This leads to increased amounts of construction and demolition (C&D) wastes. Most of the C&D wastes are reusable and recyclable. However, without proper waste management these wastes are mostly dumped into landfills without being sorted. This study utilizes a system dynamics (SD) approach to examine the feasibility of the reverse logistics implementation in C&D waste management in the long term. The focus material is paper waste, as it is one of the major wastes that can be recycled and remanufactured. The dynamic model consists of three reverse logistics options, including landfill, recycled, and remanufactured options. Costs involved in the implementation are labor, transportation, landfilling, recycling, and remanufacturing costs. Benefits, on the other hand, include sales of recycled and remanufactured products, energy savings, and green image savings. The simulation results reveal that the reverse logistics program should be implemented for at least three years to achieve positive net profit. The implementation should also be continued until the end of year 9 to be worth the investment, with the internal rate of return exceeding 12%.It is also suggested that the recycling and remanufacturing options should be promoted in long term in order to save landfill space and promote green image of the industr

Feasibility study of reverse logistic of steel waste in the construction industry

Construction and demolition (C&D) waste are increasing due to population and economic growth. Most of C&D waste materials, including steel waste, can be managed with the reverse logistics (RL), including directly reuse, recycling, and remanufacturing. However, most waste is dumped into landfills which cause environmental problems. This study examines the implementation of reverse logistics of steel waste in the construction industry utilizing a system dynamics approach. The dynamic model consists of six sub-models. The simulation results reveal that in the initial years, the net profit value of the RL implementation program is negative due to high investments in labors, trucks, and machines. It takes five years for the net profit to be positive, and eight years to achieve the internal rate of return of 12%. The construction company can use the developed dynamic model as a guideline to better understand RL implementation and plan for better implementation programs

Long-term trend of electric vehicle sales in Thailand

This research study aims at examining the long-term trend of EV sales in Thailand, utilising the system dynamics (SD) modelling approach. This approach is commonly used to model complex systems with causal relationships among key factors within the system. The developed SD model consists of five key factors affecting electric vehicle (EV) sales, namely, the environment, economy, charging infrastructure, government support, and battery maintenance. The simulation results show the increase in EV sales by ten times in the next 20 years with implementation plans related to the five key factors. The government support factor is the most important in enhancing EV sales in the short term. Several government support plans should be initiated to attract more EV consumers, such as subsidies and tax reductions. The environment and charging infrastructure factors are crucial to increasing EV sales in the long term. The enforcement of the CO2 tax and the provision of charging stations all around the country should be established to achieve a sustainable EV market in the long term. This research study contributes to the Thai government and automotive industry to better understand the complex relationships among key factors affecting EV sales. The related sectors may use the study results to plan for EV campaigns to promote the use of EVs and achieve a sustainable EV market

Long-Term Strategies for Multimodal Transportation of Block Rubber in Thailand

Thailand is one of the world’s leading exporters of block rubbers, mainly used in the automobile industry. The country strives to produce a better quality of block rubber and deliver the products to the industry, at competitive prices, to maintain its competitiveness and move ahead with sustainable growth. The government promotes a multimodal transportation to reduce logistics costs and increase the transportation network efficiency. This study develops a system dynamics (SD) model of the multimodal transportation of block rubber transportation in Thailand, to examine the different mode combinations of block rubber transportation in the long term. The results confirm using multimodal transportation (i.e., truck-ship and truck-train modes) to minimize the final logistics cost of the block rubber transportation from the growing areas to the export point, in the long term. Multimodal transportation can save up to half the final logistics costs, compared to the truck-only mode. The truck-ship and truck-train mode combinations are preferred in the southern and northeastern regions, respectively, as they provide the lowest logistics costs, in the long term. With government supports in port expansion, double-track enlargement, and access roads to ports and railway stations, multimodal transportation is expected to reduce the final logistics cost by half each year. All of these raise the country’s competitiveness on a global scale and achieve a sustainable growth and development of block rubber products in the long term. The developed SD model provides a guideline for the multimode selection of block rubber and other agricultural products with bulk transportation, to achieve the lowest logistics cost and enhance the transport efficiency, in the long term

Development of a municipal solid waste dynamic model in Bangkok, Thailand

With the growing trend of municipal solid waste amount, Bangkok now faces a number of environmental problems. To properly manage wastes and plan for an effective waste management program in the long term, this study developed a municipal solid waste dynamic model with three involved parties: 1) the “Householder”, 2) the “Government Officer”, and 3) the “Scavenger”. The relationships among the three key parties are examined through simulation results. The results indicate that, with the cooperation of all three parties, recyclable wastes can be completely sorted in 17 years. Policy testing is also conducted to effectively plan for recycling program implementation. The results reveal the importance of householder cooperation to successfully implement such a program. The developed dynamic model helps in better understanding the MSW situation in Bangkok, and plan for effective waste management

Dynamics of pertinent project delay variables in the Thai construction sector: mathematical analysis

Project completion behind schedule is a struggle for the construction sector, affecting time, cost, and quality. This investigation has been necessitated by the lingering nature of project delay risks despite many extant analyses. This study collated expert opinions from the Thai construction sector on salient construction delay variables and their influence on each other for DEMATEL-SD analysis. The collated data were analysed and found consistent with a Cronbach’s alpha of 0.939. Then, the DEMATEL technique was used to establish the influence weight of factors for the System dynamics (SD) analysis. It was discovered that minimising the design error at the preconstruction stage significantly reduces the magnitude of delay. Increasing values of design error and change order increase the rework profile. Besides, the project delivery within the scheduled 232 weeks can be ensured by minimising the threat of design error, design change, change order, rework, productivity problem, and by improving project management. This study adopted a hybrid mathematical system to holistically examine the construction delay risk by comprehensively exploring the dynamics of influencing variables and investigating their impact on the project scheme. The system helps project stakeholders to arrive at an effective decision in overcoming delay risks, thus minimising the cost overrun and improving the project quality

Assessment of Construction Competitiveness through Knowledge Management Process Implementation

In the turbulent construction market, the knowledge management process (KMP) is one of the most valuable tools of sustainability to help construction companies deal with dynamic changes and enhance their construction competitiveness (CC). To effectively utilize KMP in construction, this study aims to explore the interrelationships between key KMP factors and their influences on the CC, utilizing the structural equation modeling (SEM) approach. The objectives include extracting key KMP factors necessary for the CC enhancement, identifying direct and indirect relationships between the KMP and CC factors, and developing a self-assessment form to assist construction companies in evaluating their KMP performance and planning for long-term improvement. The results show that the five key KMP factors, namely knowledge utilization (KU), knowledge dissemination (KD), knowledge responsiveness (KR), knowledge storage (KS), and knowledge acquisition (KA), have direct and indirect effects on CC and that the feedback of CC is sent back to KMP factors for continuous improvement. The KU factor is crucial for short-term improvement. Construction companies should utilize stakeholders’ current practices and experiences to solve problems, conclude lessons learned, and pinpoint practices for future uses. The KS factor, on the other hand, should be emphasized for long-term plans to enhance KMP implementation and CC achievements. A long-term investment plan should be initiated in the database system to properly and effectively implement digital transformation in the 4.0 Era. The self-assessment form developed from the study results assists construction companies in assessing their KMP implementation and planning for sustainable development

Decision-making on reverse logistics in the construction industry

With the growing competition, many construction organizations attempt to improve their productivity, quality, and efficiency. Construction waste management, by means of reverse logistics, becomes a key issue to improve the productivity, and raise the company’s green image. In this study, four reverse logistics methods-direct reuse, remanufacturing, recycling, and landfill-are considered to manage construction and demolition (C&D) waste. Two factors (economic and site-specific) with their 15 sub-factors affecting the decisions to implement the reverse logistics are examined. The hierarchy model of reverse logistics decisions, developed through the analytic hierarchy process, reveal the importance of the economic factor over the site-specific factor. It is suggested that the transportation cost, the processing cost, the specific sorting technology, and the limited project time must be first considered before making decisions on reverse logistics plans. The construction company can utilize the developed hierarchy model to decide on the most appropriate reverse logistics plan to achieve the best benefits

Interrelationships among key profit factors of Vietnamese residential projects using structural equation modeling

This study aims to examine profit factors and their interrelationships to help real estate companies make effective project development decisions. The analysis results from questionnaire responses in 75 real estate companies, located in Ho Chi Minh City, Viet Nam, confirm five key profit factors with 16 associated variables. Interrelationships among the key profit factors were also investigated through a structural equation modeling. The variables, including population, income, transaction rate, construction cost, and construction loan’s interest rate variables, were found crucial in developing a profit enhancement plan. Strong relationships among five key profit factors were also discovered. The housing finance factor, for example, has a strong positive relationship with the housing supply factor, but a negative relationship with the buyer capacity factor. The study results help real estate companies to better understand the profit factors, and make a better profit improvement plan