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Architecture, engineering and construction (AEC) is an important industry worldwide and one of the largest economic sectors in several developing countries, particularly in Iran. The Iranian AEC sector suffers from low productivity and needs to adopt building information modeling (BIM) to reduce inefficiencies. Therefore, this paper was conducted to identify the BIM barriers and propose practical solutions to overcome them in Iran.

A comprehensive literature review, two rounds of the Delphi technique and semi-structured interviews with 12 Iranian experts in the AEC sector were conducted. The data were analyzed using the mean score, standard deviation and nonparametric tests.

The present study identified 26 BIM barriers in the Iranian AEC community and provided practical strategies for improving BIM adoption. The identified barriers were categorized into six main groups including source barriers, financial barriers, unawareness barriers, organizational barriers, regulatory barriers and market-demand barriers. The main three BIM barriers in Iran were the lack of government intervention, change-resistant and the gap between industry and academia. Kruskal–Wallis tests revealed that there are no statistically significant differences in perceptions of BIM barriers between respondents. The Mann–Whitney test indicated that there is no statistically significant difference in perceptions between engineers and architects except for one.

There are few studies on BIM adoption across developing countries, particularly in Iran. Moreover, the results can also be used in other developing nations with similar conditions.

This study leverages an enhanced expectation confirmation model of information technology continuance to explore the factors that shape the continuance intention toward cloud computing services.

Data were collected from personal cloud computing service users in Malaysia, resulting in a total of 567 usable responses. The research used partial least squares structural equation modeling (PLS-SEM) for comparative analysis and model selection based on predictive accuracy.

The study findings demonstrate that perceived benefits, ease of use, usefulness, risk and trust play crucial roles as antecedents to user confirmation and satisfaction, thereby influencing the intention for continuous service usage. Notably, the hypotheses formulated for the study received robust support, with 13 out of 14 anticipated relationships proving statistically significant.

This study presents a novel investigation into the continuance of personal cloud computing services among Malaysian users, contributing to a deeper understanding of user intention dynamics in this context. Integrating an expanded ECM-IT framework offers a comprehensive analytical approach that simultaneously considers information systems and non-IS factors. Additionally, the study underscores the significance of predictive capability assessment using the PLSpredict method, providing a valuable benchmark for model selection in future research.

To maximize the network total profit by calculating the difference between costs and revenue (first objective function). To maximize the positive impact on the environment by integrating GSCM factors in RL (second objective function). To calculate the efficiency of disassembly centers by SDEA method, which are selected as suppliers and maximize the total efficiency (third objective function). To evaluate the resources and total efficiency of the proposed model to facilitate the allocation resource process, to increase resource efficiency and to improve the efficiency of disassembly centers by Inverse DEA.

The design of a closed-loop logistics network for after-sales service for mobile phones and digital cameras has been developed by the mixed-integer linear programming method (MILP). Development of MILP method has been performed by simultaneously considering three main objectives including: total network profit, green supply chain factors (environmental sustainability) and maximizing the efficiency of disassembly centers. The proposed model of study is a six-level, multi-objective, single-period and multi-product that focuses on electrical waste. The efficiency of product return centers is calculated by SDEA method and the most efficient centers are selected.

The results of using the model in a case mining showed that, due to the use of green factors in network design, environmental pollution and undesirable disposal of some electronic waste were reduced. Also, with the reduction of waste disposal, valuable materials entered the market cycle and the network profit increased.

(1) Design a closed-loop reverse logistics network for after-sales services; (2) Introduce a multi-objective multi-echelon mixed integer linear programming model; (3) Sensitivity analysis use Inverse-DEA method to increase the efficiency of inefficient units; (4) Use the GSC factors and DEA method in reverse logistics network.

A large portion of the public building projects in Jordan suffers from sustainability performance issues. Therefore, this research aims to develop a hybrid procurement framework to enhance the implementation of BIM in the Jordanian public sector for better sustainable building performance. This study also aims to identify the influence of procurement factors on BIM adoption and usage in the public sector in Jordan and to provide a holistic picture of recent research on technology acceptance and adoption in the construction industry.

A qualitative approach was adopted using semi-structured interviews with key stakeholders (n = 12) in Jordan to explore procurement routes issues facing the adoption of BIM and to find proposed measures. Then, the findings of the interviews analysis using conventional content analysis and literature review were used based on a problem-solving approach to develop a hybrid conceptual procurement framework for BIM uptake to enhance the sustainability of building performance. Subsequently, semi-structured interviews were conducted to validate and refine the proposed conceptual procurement framework.

It was revealed that the deployment of unfavourable construction procurement approaches represents a major hurdle towards BIM implementation. Though essential for enhancing BIM implementation, it is revealed that a fundamental change from the common Design bid build (DBB) to more collaborative procurement approaches remains infeasible in view of the realities that govern the construction industry. Moreover, this study has found the key procurement approach challenges for effective BIM implementation.

Research is limited to the public sector in Jordan and further qualitative and quantitative testing of the conceptual procurement framework is needed to adjust the framework before large-scale testing.

The developed conceptual procurement framework is the first of its kind and draws a set of procurement approach remedies for the Jordanian public sector to foster the implementation of BIM.

The purpose of this paper is to illuminate the ethical concerns associated with the use of artificial intelligence (AI) in the medical sector and to provide solutions that allow deriving maximum benefits from this technology without compromising ethical principles.

This paper provides a comprehensive overview of AI in medicine, exploring its technical capabilities, practical applications, and ethical implications. Based on our expertise, we offer insights from both technical and practical perspectives.

The study identifies several advantages of AI in medicine, including its ability to improve diagnostic accuracy, enhance surgical outcomes, and optimize healthcare delivery. However, there are pending ethical issues such as algorithmic bias, lack of transparency, data privacy issues, and the potential for AI to deskill healthcare professionals and erode humanistic values in patient care. Therefore, it is important to address these issues as promptly as possible to make sure that we benefit from the AI’s implementation without causing any serious drawbacks.

This paper gains its value from the combined practical experience of Professor Elhassan gained through his practice at top hospitals worldwide, and the theoretical expertise of Dr. Arabi acquired from international institutes. The shared experiences of the authors provide valuable insights that are beneficial for raising awareness and guiding action in addressing the ethical concerns associated with the integration of artificial intelligence in medicine.