Project risk management in Iranian small construction firms

The objective of this study is to evaluate RM in small projects in Iran using identification of status, barriers, and the impact of RM on project performance. In this study, theoretical foundations and research literature were first developed through library, and then a questionnaire about these variables was designed and distributed among a number of experts in the active construction companies. Data were collected from 40 projects submitted by 25 experts from 5 executive companies. According to the studies, 10 barriers are identified as major obstacles to RM implementation in such projects, prioritized as follows: (1) lack of potential benefits, (2) not economical, (3) lack of time, (4) lack of budget, (5) lack of knowledge, (6) lack of government legislation, (7) lack of manpower, (8) low profit margin, (9) complexity of analytical tools, and (10) competition among SMCs. The findings of this research can provide an in-depth understanding of RM in small projects in Iran and make benefits of RM convincing to the participants of small projects.

Risk Factor Recognition for Automatic Safety Management in Construction Sites Using Fast Deep Convolutional Neural Networks

Many industrial accidents occur at construction sites. Several countries are instating safety management measures to reduce industrial accidents at construction sites. However, there are few technical measures relevant to this task, and there are safety blind spots related to differences in human resources’ capabilities. We propose a deep convolutional neural network that automatically recognizes possible material and human risk factors in the field regardless of individual management capabilities. The most suitable learning method and model for this study’s task and environment were experimentally identified, and visualization was performed to increase the interpretability of the model’s prediction results. The fine-tuned Safety-MobileNet model showed a high performance of 99.79% (30 ms), demonstrating its high potential to be applied in actual construction sites. In addition, via visualization, the cause of the model’s confusion of classes could be found in a dataset that the model did not predict correctly, and insights for result analysis could be presented. The material and human risk factor recognition model presented in this study can contribute to solving various practical problems, such as the absence of accident prevention systems, the limitations of human resources for safety management, and the difficulties in applying safety management systems to small construction companies.

DEVELOPING OF SUSTAINABLE SUPPLY CHAIN MANAGEMENT INDICATORS IN CONSTRUCTION

Most of the existing supply chain management methods and systems are being transferred to construction sphere regardless of the specifics of companies in the construction sector. Numerous complex factors such as ecological, social and economic are required for the continuous evaluation in the modern management of construction sector. The provided studies and the research to examine sustainable supply chain management in construction sector from a holistic perspective, concentrating on mostly longterm sustainable decision­making by the construction company rather than being centered only on the supply chain management for construction projects. This paper identifies a list of sustainability indicators for examining the supply chains of construction companies. Those indicators were categorized and assigned to one or a couple groups by reviewing their use in the previous literature agreeing to the reasoning to way better reflect the SSCM principle of their use in construction companies. The use of indicators can help develop strategies for the construction sector for sustainable policy makers and construction company managers.

Determinants of financial performance in Albanian economic entities, case of construction industry in Albania

Financial performance mainly reflects the overall financial health of the business sector over a period of time. It shows how well an entity is using its resources to maximize shareholder’s wealth. Although a thorough assessment of a firm's financial performance takes into account many other measures, the most common performance measurement used in the area of finance are financial ratios. This paper provides a comprehensive study of the financial performance measurement literature related to the construction sector in Albania. The literature covers studies from Albania, Iran, India and Pakistan, but some international evidence has also been presented. The construction sector is chosen because of its impact on economic growth in Albania, it represents the second main sector according to its share effect on Albanian GDP. The financial ratios used to measure the financial performance of the construction sector are the debt ratio, the liquidity ratio and the profitability ratio from the period 2018-2020 for 100 construction companies in Albania. Return on Assets (ROA) is taken as the predictor variable and three financial ratios are taken as the predictive variables. This research reveals that the financial ratios have positive correlation with the dependent variable whereas the leverage ratio has negative correlation. To overcome the limitations of the forthcoming studies, the considered number of years need to be increased and other models such as Market Value Added, Capital Asset Pricing Model and Economic Value Added can be used to be tested for research to analyze other factors that may affect financial performance.

THEIA

THEIA provides technical solutions for the construction industry, specializing in materials for thermal insulation. It is positioned in the middle of the distribution channel, between manufacturers and construction companies, and the profound changes that occurred in the sector had repercussions on the company's activity, forcing it to rethink its business strategy. THEIA repositioning was studied according to a specific methodology, combining analysis techniques to assess organizations' internal capacity and the exploration of external conditioning factors. The strategic plan used financial and commercial information from THEIA and from the sector where it operates, according to the following steps: analysis of THEIA's internal situation, external positioning of THEIA in the national market, definition of strategic objectives, elaboration of scenarios and recommendations.

Applying appropriate models to predict bankruptcy for Vietnamese listed construction companies

This study focuses on assessing the suitability and condition of various bankruptcy risk models applied to construction companies listed on the Vietnam Stock Market. In this study, the panel data were collected from the disclosed financial statements of the companies from 2012 to 2017. Through the assessment, bankruptcy risks are predicted for the companies that are experiencing initial signals such as delisting, compulsory supervision. In the next step, interviews were conducted to justify which of the following factors may indicate the companies at the risk of being bankrupted: asset management, capital structure, business size, and/or state management.

Bluetooth-Tracing RSSI Sampling Method as Basic Technology of Indoor Localization for Smart Grid

In recent years, Smart Grid have become the center of interest for IT companies and construction companies and various types of Smart Grids have been made currently available on the market. Yet, equipment is costly and it is not easy to convert existing equipment for Smart Grid application as they may require additional resources which could also inflict much costs. The extra costs involving the remodeling of existing housing structure and installment of new equipment can be avoided by using advanced wireless technologies. As an example, this book proposed an indoor localization system that adopts Bluetooth technology and uses RSSI (Received Signal Strength Indication) values for localization. Researchers have configured a system where the central control device will recognize all other devices or equipment in the system, communicate with each other, and respond to the commands or the information provided. However, despite the efforts of many researchers, existing RSSI-based indoor localization systems do not show a satisfactory level of accuracy such that we have devised a system that traces the trend in the RSSI samples.