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This study aims to examine the challenges facing the construction industry practitioners toward adopting digital construction technologies in the Jordanian construction industry.

Quantitative methods were used by reviewing the related literature to include 16 challenges that face the Jordanian construction industry in adopting digital construction. A questionnaire was used to achieve the desired study objectives for 373 respondents from various institutions and companies. The questionnaire was analyzed with SPSS using statistical tests such as mean score, Kruskal–Wallis H test and factor analysis.

After collecting the quantitative data, the study showed that the most challenges facing construction industry practitioners toward adopting digital construction techniques are lack of qualified workers, high requirement for computing equipment’s, high initial cost of bringing these technologies to the market and construction firms low investment in research and development. These challenges faced by respondents were divided into three main factors, namely, construction’s nature, financial constraints and poor management support.

This study provides information and statistics on the challenges that face individuals or companies toward adopting digital construction techniques in Jordan. It proposes recommendations and proper practical implantation strategies to overcome the challenges.

This paper aims to identify and provide a theoretical explanation for the barriers that hinder the adoption of emerging technologies in the architecture, engineering and construction industry, irrespective of the company’s size, specialization or geographical location. In addition, the paper proposes potential areas for future research in this domain.

A list of barriers hindering the adoption of emerging technologies was identified and clarified using a systematic literature review of various scientific sources.

Twenty-five barriers were recognized and explained and some suggestions for future research studies were provided.

The barriers related to a specific country or region or to a specific technology were excluded.

By providing a deeper comprehension of the barriers hindering the adoption of emerging technologies, this review is expected to encourage their adoption in the industry. Furthermore, it could prove valuable in devising effective strategies for the successful implementation of these technologies.

The construction industry sector is developing rapidly, especially with the increasing pace of the Fourth Industrial Revolution in this sector. Construction projects can benefit from greater integration and collaboration between their technologies and processes to reap the advantages and keep pace with the recent significant technological and managerial techniques developments. Therefore, this study aims to delve into and investigate building information modeling (BIM) and Lean Construction (L.C.) with a concentration on the potential BIM–lean interactions synergy and integration in the Jordanian construction industry.

This study takes exploratory nature, followed by the deductive research approach, and is designed to be a mono-quantitative research methodology. Moreover, the sampling technique is non-probability convenience sampling, and the research strategy is implemented through a questionnaire used and analyzed by using Statistical Package for Social Science to conduct descriptive and inferential statistical analysis and verify the reliability and validity through proper tests.

The BIM–lean interactions synergy and integration findings revealed that eliminating waste (time, cost, resources), promoting continuous improvement (Kaizen) and standardizing as lean construction principles are the most significant and agreeable toward achieving BIM–lean interactions synergy. On the other hand, “High 3D Visualization Modelling” was the most significant BIM function, followed by “Rapid and Auto-Generation of Documents and Multiple Design Alternatives” and “Maintenance of Information and Design Model Integrity.” Moreover, based on the relative importance index (RII) values, “Lack of Technical Expertise in BIM-LEAN” is the most significant challenge with a 0.89 value of RII, followed by “Lack of Government Direction and Standard Guidelines” with a 0.88 value of RII and “Financial considerations” with a 0.83 value of RII.

This study will help provide a new detailed overview that investigates the effects and expected benefits of integrating BIM processes and technological functionalities with lean construction principles within a synergetic environment. Moreover, the study will increase the awareness of using new technologies and management approaches in the architectural, engineering and construction industry, seeking to achieve integration between these technologies to reach ideal results in terms of the outputs of construction operations.

The process of predicting construction costs and forecasting price fluctuations is a significant and challenging undertaking for project managers. This study aims to develop a construction cost index (CCI) for Jordan’s construction industry using fuzzy analytic hierarchy process (FAHP) and predict future CCI values using traditional and machine learning (ML) techniques.

The most influential cost items were selected by conducting a literature review and confirmatory expert interviews. The cost items’ weights were calculated using FAHP to develop the CCI formula.

The results showed that the random forest model had the lowest mean absolute percentage error (MAPE) of 1.09%, followed by Extreme Gradient Boosting and K-nearest neighbours with MAPEs of 1.41% and 1.46%, respectively.

The novelty of this study lies within the use of FAHP to address the ambiguity of the impact of various cost items on CCI. The developed CCI equation and ML models are expected to significantly benefit construction managers, investors and policymakers in making informed decisions by enhancing their understanding of cost trends in the construction industry.

Demand forecasts are a key component of planning efforts and are crucial for managing core operations. This study aims to evaluate the use of several machine learning (ML) algorithms to forecast demand for residential construction in Jordan.

The identification and selection of variables and ML algorithms that are related to the demand for residential construction are indicated using a literature review. Feature selection was done by using a stepwise backward elimination. The developed algorithm’s accuracy has been demonstrated by comparing the ML predictions with real residual values and compared based on the coefficient of determination.

Nine economic indicators were selected to develop the demand models. Elastic-Net showed the highest accuracy of (0.838) versus artificial neural networkwith an accuracy of (0.727), followed by Eureqa with an accuracy of (0.715) and the Extra Trees with an accuracy of (0.703). According to the results of the best-performing model forecast, Jordan’s 2023 first-quarter demand for residential construction is anticipated to rise by 11.5% from the same quarter of the year 2022.

The results of this study extend to the existing body of knowledge through the identification of the most influential variables in the Jordanian residential construction industry. In addition, the models developed will enable users in the fields of construction engineering to make reliable demand forecasts while also assisting in effective financial decision-making.

There is little information existing about the spread of lean among Jordanian construction companies. Building on a report by Diekmann et al. (2004), this paper aims to perform a similar investigation among first-grade Jordanian construction companies to assess the extent of implementation of lean techniques.

For this purpose, a quantitative approach to measuring contractors’ conformance to lean practices was adopted. A survey of 61 contractors was conducted using both e-mails and personally delivered surveys that were completed on the spot. The results were analysed, and a practice value index, which indicates the level of implementation, was figured out for lean practices. In addition, an analysis of variance was conducted to determine whether there were differences among respondents from different construction fields.

The survey indicated that some procedures used by Jordanian contractors were consistent with lean construction practices. However, there was no proof that lean concepts were used on a company-wide basis. Furthermore, the survey revealed that the Jordanian construction industry lacks a “continuous improvement“ mentality, suffers from the absence of error proofing devices and provides minimal training at several levels of the organisation.

The outcomes of the study are valuable for contractors and developers of management practices, as it will encourage them to adopt lean construction holistically and identify features that are not exploited in the Jordanian construction industry.

The purpose of this paper is to identify drought conditions in Jordan in the period 1960‐2006 for two major basins – the Yarmouk and the Zarqa. This study aims to look at the long‐term drought conditions (hydrological droughts) and to investigate the possibility of changes in the monthly precipitation pattern for the period of 1997‐2006, as this period has suffered from the average slightly dry conditions for the two basins.

The Standard Precipitation Index (SPI) is used to assess drought conditions in the Yarmouk and Zarqa basins. The SPI is applied on an annual basis to assess the hydrological long‐term droughts. Average monthly precipitation is used as the input to the SPI procedure.

The SPI is applied on an annual basis (12 months) SPI‐12. Results of the SPI‐12 assessment show that the years 1978, 1995, and 1999 represented extremely dry conditions in both basins. The years 1989 and 1993 represented severely dry conditions in the Zarqa basin and extremely dry conditions in the Yarmouk basin. The statistical procedure for precipitation anomalies identifies precipitation anomalies for the years 2000, 2003, and 2006. However, due to the limited number of anomaly years this study does not conclude that there is a change in the pattern of monthly precipitation of the tested period 1997‐ 2006.

Using the SPI method this work can be extended to compare drought conditions in the remaining major basins in the country.

The paper provides important information about drought conditions in Jordan and ways to assess precipitation anomalies and pattern changes. This can be beneficial to the planning of water resources in Jordan and the associated developments (agricultural, industrial, tourism, and residential).

This study aimed to provide a framework that includes the principles of sustainable construction to evaluate their application in the construction of government building projects in various environmental, economic, and social aspects distributed over the project phases throughout its life cycle.

Qualitative methods from literature review and analysis of sustainability assessment tools were used to design the framework. The designed framework included six main categories, comprising 19 indicators that include sustainable building principles to assess application levels in government construction projects. It was used to evaluate applying sustainability practices in Jordanian government construction projects. 133 questionnaires were distributed to a convenience sample of three government institutions concerned with the design, implementation, and management of government buildings in Jordan.

After collecting the quantitative data, the results showed that there is an application of six sustainability principles during the initial planning, analysis, and design stages of Jordanian government construction projects. The results focused on the application levels in social sustainability principles versus environmental and economical, especially in the operating stages during the project life cycle.

This study contributes by providing a tool to evaluate the sustainability of government construction projects and increase the efficiency and effectiveness of these types of buildings in both the short and long term by making them more sustainable. Subsequently, recommendations are made on reorienting government construction projects toward a sustainable building approach.

The purpose of this paper is to identify factors affecting cost estimate accuracy in each of five design stages preceding building construction: order of magnitude, conceptual/schematic, detailed design, construction document and bid phase.

Data were collected using an online survey completed by 138 respondents who work in design consultancy firms in Jordan, including project managers, architects and quantity surveyors (QSs). Survey responses were analyzed using descriptive statistics. Confirmatory interviews and case study comparisons were used to confirm the statistical analysis results.

The results of this study indicated that each design stage’s cost estimate was affected by several factors. Two significant factors were common across four of the five design stages: client experience and project team experience. In addition, a high level of agreement was observed among the project managers, architects and QSs regarding the factors affecting cost estimate accuracy.

Accurately estimating building construction costs during the design process has posed a challenge for designers and their clients in Jordan. Despite the care and effort involved in preparing cost estimates in each of the five design stages, deviations are commonly observed. Because the accuracy of building construction cost estimates directly affect the success or failure of a project, the results of this study can be used to reduce uncertainties in building construction cost estimation and subsequently increase the likelihood of project success

Despite the enormous need to succeed in the urban model, scientists and policymakers should work consistently to create blueprints to regulate urbanization. The absence of coordination between the crucial requirements and the regional strategies of the local authorities leads to a lack of conformance in urban development. The purpose of this paper is to address this issue.

This study intends to manage future urban growth patterns using integrated methods and then employ the results in the genetic algorithm (GA) model to considerably improve growth behavior. Multi-temporal land-use datasets have been derived from remotely sensed images for the years 1990, 2000, 2010 and 2020. Urban growth patterns and processes were then analyzed with land-use-and-land-cover dynamics. Results were examined for simulation and utilization of the GA.

Model parameters were derived and evaluated, and a preliminary assessment of the effective coefficient in the formation of urbanization is analyzed, showing the city's urbanization pattern has followed along with the transportation infrastructure and outward growth, and the scattering rates are high, with an increase of 5.64% in building area associated with a decrease in agricultural lands and rangelands.

The research achieved a considerable improvement over the growth behavior. The conducted research design was the first of its type in that field to be executed to any specific growth pattern parameters in terms of regulating and policymaking. The method has integrated various artificial intelligence models to monitor, measure and optimize the projected growth by applying this design. Other research on the area was limited to projecting the future of Amman as it is an urbanized distressed city.