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Successful risk management is influential in different phases of construction projects. It can play a critical role in reducing the possibility of claims as well as related disputes. The risk management knowledge area in large capital projects such as oil and gas is considered a questionable problem in the construction industry. The present study makes an effort to identify the importance of process groups in improving risk management performance.

This study is selected and ranked 36 factors leading to the claim in Iran's oil and gas industry through the Delphi method and a questionnaire. Factors categorized into a risk breakdown structure (RBS) include eight groups. Factors are linked to one of the process groups by a Delphi method. Finally, the relationship between RBS and the five process groups is analyzed using partial least squares structural equation modeling (PLS-SEM).

Findings showed that the planning process group had more confirmed factors than others. Most of the supported communications belonged to the contractor and the owner parties. Also, the cause of delay in the implementation phase due to the contractor performance had a higher relative importance index.

This article, from a project life-cycle perspective, considers the new structure between the risks leading to claims and the key parties to the project. It can be a good criterion for identifying risks and a timelier response to them before the risks turn into disagreements.

The present study aims to develop a risk-supported case-based reasoning (RS-CBR) approach for water-related projects by incorporating various uncertainties and risks in the revision step.

The cases were extracted by studying 68 water-related projects. This research employs earned value management (EVM) factors to consider time and cost features and economic, natural, technical, and project risks to account for uncertainties and supervised learning models to estimate cost overrun. Time-series algorithms were also used to predict construction cost indexes (CCI) and model improvements in future forecasts. Outliers were deleted by the pre-processing process. Next, datasets were split into testing and training sets, and algorithms were implemented. The accuracy of different models was measured with the mean absolute percentage error (MAPE) and the normalized root mean square error (NRSME) criteria.

The findings show an improvement in the accuracy of predictions using datasets that consider uncertainties, and ensemble algorithms such as Random Forest and AdaBoost had higher accuracy. Also, among the single algorithms, the support vector regressor (SVR) with the sigmoid kernel outperformed the others.

This research is the first attempt to develop a case-based reasoning model based on various risks and uncertainties. The developed model has provided an approving overlap with machine learning models to predict cost overruns. The model has been implemented in collected water-related projects and results have been reported.

Nowadays, the recent advances in information and communications technology and the advent of Web 2.0 technology have resulted in the increasing popularity of social media and provided enterprises and companies with new horizons in establishing an effective significant relationship with clients. Despite the recognized importance of social media in knowledge management (KM) and customer relationships, there is not any research to identify social media capabilities related to customer knowledge management (CKM). Therefore, the purpose of this study is to recognize the social media capabilities related to CKM effectively.

To obtain research objectives, literature review, focus group method and expert interview were applied to identify and categorize social media capabilities. Analytical hierarchy process (AHP) also used to prioritize capabilities important.

The results indicate social media capabilities such as conversation capability, sharing capability, groups/community capability, relationship capability, speed and ease of access for the public are the main capabilities related to exploit customer knowledge and manage it successfully.

The results highlight the different social media capabilities for CKM approach which will enhance customer insight and personalized services. Because of the newness of CKM and social media implementation in Iranian firms, empirical study was not conducted for a better understanding of their business value.

The main innovation of this study is identifying the social media capabilities related to CKM and prioritizing them which allow managers to select the most appropriate social media tools based on these results.

The purpose of this study is to assess the e-readiness status of libraries in the Shahid Beheshti University of Medical Sciences in terms of four dimensions – human resources, electronical infrastructure, network services and programs and enhancers of the networked world.

The study population consists of 11 libraries of the Shahid Beheshti University of Medical Sciences, including the central library and 10 faculty libraries. The data collection instrument is a questionnaire prepared by the researchers that has been designed on the basis of the “e-readiness assessment of Iranian academic libraries model”. Depending on the respondents there are three parts to the questionnaire: questionnaire for managers, staff and information and communication technology (ICT) officials. Their reliability and validity have been proved.

The libraries of Shahid Beheshti University of Medical Sciences had an average to high status in terms of “human resources” with a score of 2.32, “electronic infrastructure” with a score of 2.48, “network services and programs” with a score of 2.09 and “networked world enhancers” with a score of 2.37 out of 4. In total, these libraries had an average to high status in terms of e-readiness, with a score of 2.29.

The findings of this study can help the library administrators and officials of Shahid Beheshti University of Medical Sciences to plan improvements to the situation of ICT.

The purpose of this study is to discover the components of virtual leadership in universities and higher education institutions during Covid-19 pandemic.

This research uses the qualitative research design, and semi-structured interviews with senior leaders were conducted with non-random purposeful and snowball sampling methods. Also, grounded theory was used for analyzing, coding and classifying the data.

After analyzing data, five main components influencing virtual leadership including leader's personality traits, followers' characteristics, technological, environmental and organizational components were identified.

As leadership, particularly virtual leadership, highly depends on context such as the level of technology in that certain region, the results cannot be generalized to other sectors or countries.

The research advances leadership development theory by highlighting the main components of virtual leadership in educational sector as a comprehensive perspective and complement the other aspects of virtual leadership such as consequences and challenges investigated by other studies.

This study aims to investigate the effect of mechanical peening on the cooling rate of a subsequently deposited layer in a hybrid additive manufacturing (AM) process.

In this experimental study, 20 layers of 316 L stainless steel are built via directed energy deposition, with the tenth layer being subject to various peening processes (shot peening, hammer peening and laser shock peening). The microstructure of the eleventh layer of all the samples is then characterized to estimate the cooling rate.

The measurements indicate that the application of interlayer peening causes a reduction in primary cellular arm spacing and an increase in micro segregation as compared to a sample prepared without interlayer peening. Both factors indicate an increase in the cooling rate brought about by the interlayer peening.

This work provides insight into process design for hybrid AM processes as cooling rates are known to influence mechanical properties in laser-based AM.

To the best of the authors’ knowledge, this work is the first of its kind to evaluate the effects of interlayer peening on a subsequently deposited layer in a hybrid AM process.