scholarly journals Model-Based Dynamic Forecasting for Residential Construction Market Demand: A Systemic Approach

2021 ◽  
Vol 11 (8) ◽  
pp. 3681
Author(s):  
Kyeong-Baek Kim ◽  
Ji-Hoon Cho ◽  
Sang-Bum Kim
Keyword(s):  
System Dynamics ◽  
Construction Industry ◽  
Demand Forecasting ◽  
Forecasting Model ◽  
Residential Construction ◽  
Future Market ◽  
Market Demand ◽  
Construction Market ◽  
Input Variables ◽  
Market Changes

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.

Approach of Cross-Country Comparisons on Residential Construction Industry for China

2014 ◽  
Vol 584-586 ◽  
pp. 2510-2513
Author(s):  
Cheng Gang Xu ◽  
San Hua Sheng
Keyword(s):  
Construction Industry ◽  
Purchasing Power Parity ◽  
Residential Construction ◽  
Purchasing Power ◽  
Power Parity ◽  
Construction Market ◽  
International Construction ◽  
Cross Country ◽  
Price Distortions ◽  
Currency Conversion

In cross-country comparisons of construction economy, the purchasing power parity index as a currency conversion coefficient can substitute for the exchange rates reduce construction price distortions. According to BOCC method, the special development conditions of residential construction industry for China and the regional differences of non-tradable goods, we propose the practices estimating purchasing power parity for the basic building, small and micro engineering between the countries of geographical proximity, which help the development of space index of China's construction cost and are an effective ways to accelerate contacts with the international construction market.

scholarly journals Deterrence of Punitive Measures on Collusive Bidding in the Construction Sector

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wenhui Zhu ◽  
Yuhang Zheng ◽  
Kunhui Ye ◽  
Qian Zhang ◽  
Minjie Zhang
Keyword(s):  
Decision Making ◽  
System Dynamics ◽  
Construction Industry ◽  
Competition Policy ◽  
Construction Sector ◽  
Deterrence Theory ◽  
Construction Market ◽  
Long Time ◽  
Severity Of Punishment ◽  
Sd Model

Collusive bidding has been a deep-seated issue in the construction market for a long time. The strategies implemented by bid riggers are deliberate, interactive, and complex, suggesting that antitrust authorities have difficulty preventing collusive behaviors. Based on game payoff matrixes, this study proposes a system dynamics (SD) model to present the deterrence of punitive measures, namely the certainty of punishment (CoP) and the severity of punishment (SoP), on regular bidders’ to-collude decision-making. Data were collected from the Chinese construction industry to test the proposed SD model. While the model was supported, the results indicate that the CoP has a greater impact than the SoP on deterring regular bidders from making to-collude decisions. Furthermore, these two punitive measures cannot be replaced by each other, given the same deterrence effects. Thus, the study demonstrates the usefulness of deterrence theory to inhibit collusive bidding in the construction sector. It also sheds some light on the formulation of competition policy from the perspective of deterrence.

Logistics demand forecasting model based on improved neural network algorithm

2020 ◽  
pp. 1-11
Author(s):  
Hongjiang Ma ◽  
Xu Luo
Keyword(s):  
Neural Network ◽  
Influencing Factor ◽  
Demand Forecasting ◽  
Forecasting Model ◽  
Logistics System ◽  
Model Based ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Demand Forecasting Model ◽  
Logistics Demand

The irrationality between the procurement and distribution of the logistics system increases unnecessary circulation links and greatly reduces logistics efficiency, which not only causes a waste of transportation resources, but also increases logistics costs. In order to improve the operation efficiency of the logistics system, based on the improved neural network algorithm, this paper combines the logistic regression algorithm to construct a logistics demand forecasting model based on the improved neural network algorithm. Moreover, according to the characteristics of the complexity of the data in the data mining task itself, this article optimizes the ladder network structure, and combines its supervisory decision-making part with the shallow network to make the model more suitable for logistics demand forecasting. In addition, this paper analyzes the performance of the model based on examples and uses the grey relational analysis method to give the degree of correlation between each influencing factor and logistics demand. The research results show that the model constructed in this paper is reasonable and can be analyzed from a practical perspective.

scholarly journals Usage of the Pareto Fronts as a Tool to Select Data in the Forecasting Process—A Short-Term Electric Energy Demand Forecasting Case

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3204
Author(s):  
Michał Sabat ◽  
Dariusz Baczyński
Keyword(s):  
Energy Demand ◽  
Demand Forecasting ◽  
Electric Energy ◽  
Forecasting Model ◽  
Short Term ◽  
Complex Evaluation ◽  
Proposed Model ◽  
Energy Demand Forecasting ◽  
Pareto Fronts ◽  
Naive Approach

Transmission, distribution, and micro-grid system operators are struggling with the increasing number of renewables and the changing nature of energy demand. This necessitates the use of prognostic methods based on ever shorter time series. This study depicted an attempt to develop an appropriate method by introducing a novel forecasting model based on the idea to use the Pareto fronts as a tool to select data in the forecasting process. The proposed model was implemented to forecast short-term electric energy demand in Poland using historical hourly demand values from Polish TSO. The study rather intended on implementing the range of different approaches—scenarios of Pareto fronts usage than on a complex evaluation of the obtained results. However, performance of proposed models was compared with a few benchmark forecasting models, including naïve approach, SARIMAX, kNN, and regression. For two scenarios, it has outperformed all other models by minimum 7.7%.

Conceptual framework of value management adoption in the Nigerian construction industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lekan Damilola Ojo ◽  
Deji Rufus Ogunsemi ◽  
Olusola Ogunsina
Keyword(s):  
Conceptual Framework ◽  
Construction Industry ◽  
Construction Projects ◽  
Value Management ◽  
Chi Square ◽  
Content Type ◽  
Construction Market ◽  
Innovative Management ◽  
Coefficient Of Concordance ◽  
Global Construction

Purpose The Nigerian construction industry is bedeviled with poor project performance and outcomes which value management (VM) could address if applied. The application of VM on Nigerian construction projects is very minimal due to certain obstacles, namely, lack of VM experts, paucity of knowledge on the techniques, etc., which inhibits the adoption into the construction industry. Therefore, this study aims to develop a conceptual framework of the adoption of VM on construction projects in a typical developing economy. Design/methodology/approach This study engaged 15 selected VM experts in two rounds of Delphi survey to develop a conceptual framework of VM adoption. The method of data analysis includes mean score, standard deviation, Kendall’s coefficient of concordance, chi-square (χ2) test, interrater agreement analysis and significant level analysis. The developed conceptual framework was sent to a team of local and international VM experts for validation. Findings This study reveals that the adoption of VM requires the collective effort of relevant stakeholders in the construction industry. The framework developed presents individual and collective activities to be undertaken by the stakeholders. The activities include training, legislation, government-funded research, etc. Thus, the adoption of innovative management methodology like VM requires the collaboration of academics, construction professional bodies and government parastatals. This will assist in the judicious use of limited construction resources and boost the relevance of the Nigerian construction industry among developing nations and in the global construction market. Originality/value This study used the opinions of few construction professionals that can be regarded as VM experts in Nigeria, as against engaging a pool of construction professionals who may not be knowledgeable in VM process. Engaging the few VM experts in the Nigerian construction industry is important to have a valid basis for drawing conclusion, as large questionnaire survey could be possibly filled by inexperienced or unqualified respondents if stringent criteria are not considered at the outset of this study.

Diagnosis of Current Employment in Architectural Student Responding to Korean Construction Market

2012 ◽  
Vol 450-451 ◽  
pp. 140-144
Author(s):  
Sang Chul Kim ◽  
Jae Hyun Lim ◽  
Jun Ho Park ◽  
Tae Hwa Jung
Keyword(s):  
Construction Industry ◽  
Supply And Demand ◽  
Current Status ◽  
Major Area ◽  
Construction Companies ◽  
Construction Market

Construction market in Korea has been decreased for 3 or 4 years, and it brought the problem in supply and demand of workforce. Therefore, new workforce in construction industry could not been enter, and some of them have been employed in non-major area. This research intends to analyze construction industry as well as demand and status of construction companies and to diagnose status of new workforce for architectural works, and a survey is conducted for enrolled students and graduates to diagnose problems of current status in order to suggest the alternatives in Korea.

scholarly journals The Housing Market Value Chain: An Integrated Approach for Mitigating Risk in Informal Residential Construction in Haiti

2020 ◽  
Vol 12 (19) ◽  
pp. 8006
Author(s):  
Christianos Burlotos ◽  
Tracy L. Kijewski-Correa ◽  
Alexandros A. Taflanidis
Keyword(s):  
Housing Market ◽  
Construction Industry ◽  
Value Chain ◽  
Market Value ◽  
Integrated Approach ◽  
Residential Construction ◽  
Implementation Framework ◽  
Middle Income ◽  
Economic Constraints ◽  
Market Value Chain

Access to dignified housing represents a critical challenge for many low- and middle-income countries (LMICs). Technical and economic constraints frequently lead homeowners in these countries toward incrementally-constructed homes, which are often proven deadly when exposed to seismic or meteorological hazards. This paper offers a holistic analysis of the informal residential construction industry contextualized in Léogâne, Haiti, the effective epicenter of the 2010 Haiti earthquake, and offers an implementation framework geared towards integrating the housing delivery process to accommodate more resilient typologies. First, the concept of the housing ecosystem is introduced, and a thorough analysis of the technical, economic, and political factors that constrain this ecosystem in Haiti is presented. The defining elements of the resulting residential construction industry are then discussed: An informal blend of Design-Build and Master Builder methods of project delivery for incrementally-constructed (and largely masonry) permanent homes. The housing ecosystem is then redefined as a seven-step housing market value chain, and interventions to further strengthen and integrate this value chain are presented for each of the seven steps. Interventions are grounded in analogous contexts and refactored specifically for the Haitian case study scenario through extensive co-creation with stakeholders in Haiti. Particular focus is given to the Léogâne Community Building Fund, a concept designed to democratize housing finance for low to middle-income groups. When implemented in an integrated fashion, risks across this housing market value chain are effectively mitigated to sustainably deliver dignified housing through a market-based approach suitable for Haiti and extensible to other LMICs.

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