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The construction industry is dynamic and often unregulated due to its complex, project-based nature. This makes the task of implementing human resource management (HRM) functions more difficult than in other economic sectors. This is particularly the case for developing countries which rely on a migrant, casual, and transient workforce. Despite offering flexibility, a transient workforce can lead to unpredictable rates of absenteeism and unsatisfactory productivity. This paper links HRM practices in the construction industry of the developing world to rates of absenteeism across three segments of the construction workforce – foremen, skilled workers, and unskilled workers. The paper aims to discuss these issues.

A survey targeting 60 construction sites in Beirut, Lebanon form the basis of the analysis. Within each site, measures of absenteeism for foremen, skilled, and unskilled workers were solicited along with other data on HRM onsite.

The results suggest a regression model for worker absenteeism based on tenure of work as well as the absenteeism of workers at the next hierarchical level onsite.

This study is among the first to show a link between the mechanisms by which construction workers are employed (contract-based foremen vs daily/weekly labourers – both skilled and unskilled) and the rate of absenteeism seen onsite. Given the role of absenteeism in construction productivity, having a good understanding of the underlying causes of absenteeism is critical to the design of mitigating policies.

Faculty play a unique role in universities performing duties along the three fronts of teaching, research and service. While it might be teaching that contributes most to the bottom line of a small university, it is often research by which faculty merit is judged. This study explores the relationships between role ambiguity, role conflict and commitment (affective, normative and continuance) as mediated by job satisfaction among faculty members.

A sample of 133 faculty members at a US-accredited university in Lebanon served as the basis for this study. The faculty members completed a survey covering scales on role ambiguity, role conflict, commitment and job satisfaction in addition to demographic variables.

We find that a decrease in role ambiguity strengthens affective and normative commitment but weakens continuance commitment. Structural equation modeling indicates that job satisfaction partially mediates the relationship between role ambiguity and affective commitment, while not mediating the relationship between role ambiguity and normative and continuance commitments. Similar findings hold for job satisfaction as a mediator in the relationship between role conflict and commitment.

Based on statistical modeling, this work (1) puts forth a revised scale for organizational commitment tailored to academia and (2) provides guidance to higher education institutions in terms of the differential impacts on faculty commitment that stem from reducing role-ambiguity versus role-conflict. Managerial recommendations focus on improving normative and affective commitment through the design of policies to reduce role conflict among faculty.

This paper uses a cognitive analytics management approach to analyze, understand and solve the problems facing the implementation of information systems and help management do the needed changes to enhance such a critical process; the emergency management system in the health industry is analyzed as a case study.

Cognitive analytics management (CAM) framework (Osman and Anouz, 2014) is used. Cognitive process: The right questions are asked to understand the behavior of every process and the flow of its corresponding data; critical data variables were identified, guidelines for identifying data sources were set. Analytics process: Techniques of data analytics were applied to the selected data sets, problems were identified in user–system interaction and in the system design. The analysis process helped the management in the management process to make right decisions for the right change.

Using the CAM framework, the analysis to the Lebanese Red Cross case study identified system user-behavior problems and also system design problems. It identified cases where distributed subsystems are vulnerable to time keeping errors and helped the management make knowledgeable decisions to overcome major obstacles by implementing several changes related to hardware design, software implementation, human resource training, operational and human-technology changes. CAM is a novel and feasible software engineering approach for handling system failures.

The paper uses CAM framework as an approach to overcome system failures and help management do the needed changes to enhance such a critical process. This work contributes to the software engineering literature by introducing CAM as a new agile methodology to be used when dealing with system failures. Furthermore, this study is an action research that validated the CAM theoretical framework in a health emergency context in Lebanon.

Employing multi-type laborers (MLs) is common in multinational and cross-culture projects (MPCs). Different attributes of MLs can lead to uncertain and dynamic laborer behaviors (i.e. behavioral diversities), which may cause project deviations. Previous studies do not consider the uncertainties or dynamics of behaviors adequately or they only provide general suggestions. The purpose of this paper is to combine system dynamics (SD) and agent-based modeling (ABM) to build an integrated model. The proposed ABM-SD can gain better understanding of MLs’ behavioral diversities, reveal the associated impacts and improve project management.

Based on extensively review in construction labor management and computer simulation, architecture is built to depict the relationships between the affecting factors of MLs’ behaviors, MLs’ behavioral diversities and project performance. Second, conceptual structures of the ABM-SD model are developed. Third, methods to implement the model in practice are introduced, focusing on data collection and model structure adjustment. Finally, the model is tested in a case study.

Different ML groups have distinctive behaviors which constantly change through interactions between MLs, engineers and external environment. Inadequate consideration of the diversities can result in inaccurate estimation of productivity, work quality and absenteeism, causing severe project deviations such as schedule delay, cost overrun and high absenteeism. On the other hand, using the ABM-SD model, the root causes of project deviations are analyzed from the perspective of MLs’ behavioral diversities and the optimization of labor management can significantly improve project performance.

This paper supplements previous studies because the ABM-SD model takes fully use of the strength of simulation of solving uncertain and dynamic problems and combines both qualitative and quantitative findings in existing studies of labor management. Besides, the ABM-SD model is also a practical management tool to better monitor laborer behaviors and forecast the impacts. The limitation is mainly about the small scale of the case study. However, the ABM-SD model already demonstrates the mechanism about how MLs’ different behaviors affect a project, which fulfill the aim of the study.

The ABM-SD model can simulate MLs’ behavioral diversities and produce reliable estimations of project performance. It also allows to optimize management plans. Furthermore, The ABM-SD model is adjustable based on specific project conditions, which make it applicable for different tasks, different laborer compositions and even different projects. Thus, the ABM-SD model can be a practical tool for engineers in MCPs.

SD and ABM are applied to study behaviors with well-known benefits in both separated and integrated manner. However, few studies use the approach to investigate MLs’ behaviors in MCPs. Hence, the proposed ABM-SD model is an original attempt to improve the laborer management level in MCPs.

Planning phase of a project results to series of crucial decisions which determine the path to objectives achievement. At the same time, in this phase, project encounters the highest level of uncertainty in comparison of all phases of project lifecycle. This paper aims to support early decisions of project based on the progress forecasting.

The scope of study is limited to downstream projects of petroleum industry in Iran, and the proposed model is trained and tested based on 75 Iranian completed petroleum projects. First, types of progress curve functions are investigated, and various types are studied and the most appropriate ones are selected through curve fitting. In the next step, using questionnaire, dependent and independent variables are recognized. Finally, using historical data and s-curve generator functions, a fuzzy inference system (ANFIS) based model have been developed to support early phases decision-making processes.

Based on the analysis of received questionnaires, six functional criteria in two groups as dependent variables and 25 independent variables, in two groups and four clusters are determined and categorized. Eventually, performance prediction model of a project has been developed by using Adaptive Nero Fuzzy Inference System.

The main contribution of this study to construction management knowledge is categorizing two groups of variables, which first one defines the project dynamic and the other calculates the key effects on previous one. Also, this investigation improves the current knowledge by analyzing the project system from the dynamic behavior perspective and modeling the defined variables using ANFIS tools.

The purpose of this paper is to focus on productivity as it unfolds during the execution of a particular task, i.e., reinforced concrete operations. The main aim is understanding whether the learning effect explaining the improvement of productivity in subsequent cycles of a given repetitive construction process is mainly attributable to a pure worker learning (independent on the specific site) or to the experience developed by the crew on the site conditions.

The authors conduct a research that empirically investigates and compares the change in productivity data of a single worker during his/her working life and that of a crew involved in specific repetitive work, such as the concreting activities of a multi-storey building.

The findings suggest differentiating between productivity gain as a result of the learning effect of the individual worker throughout his/her working life (which is independent of the specific project and site) and that of a crew composed by more workers which repeat reinforced concrete operations in a given specific project.

Despite the great attention reserved to learning in construction, few researchers discuss on the real applicability of the learning curve (LC) theory in the construction industry. The authors contribute to this literature by empirically investigating the contributions that the learning effect of the individual worker and that of a crew repeating a given task (i.e. reinforced concrete operations) in a given project have on the productivity improvement for subsequent cycles of the repetitive construction process.

The findings of this study have important managerial implications. The shape of the LC of the individual worker implies that learning increases relatively slowly in his/her working life (particularly after one to two years), while the effects of the crew experience are immediately significant in a time range of few weeks. This means that a single “one-off” multi-storey building project will show in the first storey the “historical,” individual productivity of the individual workers (i.e. not going to vary significantly in the next few weeks). The productivity improvement in the further storeys will only depend on the project-specific (and collective, for the crew) “learning” due, for example, to better coordination or to other issues that are progressively solved moving from the first storey to the following ones. So, the project-specific LC increases in a faster way than the individual one, and the overall productivity can be improved by accelerating the project-specific learning rate with more accurate project-specific design and management.

This paper enhances the understanding of the contributions that the learning effect of the individual worker and that of a crew repeating a given task (i.e. reinforced concrete operations) in a given project have on the productivity improvement for subsequent cycles of the repetitive construction process. This will contribute to improve the planning and control of site work activities, avoiding time and money wastefulness.

Engaged employees are a critical asset in any business. This is largely because engaged employees tend to proffer innovative solutions to complex problems in the workplace. The purpose of this paper is to examine the relationship between engagement and innovation as moderated by the use of 360-degree evaluation.

A survey targeting employees in Lebanon solicited their perceptions of 360-degree evaluation, engagement and innovative behaviors along with a statement as to whether their firm used 360-degree evaluations or not. Structural equation modeling (SEM) was used to test the moderating effect of 360-degree evaluations on the latent variables of engagement and three facets of innovation.

SEM results show that 360-degree evaluations serve to enhance engaged employees’ innovative work behavior. However, ideation (creation and implementation) behaviors are more strongly influenced by the presence of 360-degree evaluation as compared to their “tangible” counterpart (technology and financial resource use).

Respondents selected for this research were randomly sampled employees in Lebanon. A stronger study strategy would be to study paired departments within organizations – one implementing 360-degree evaluation and another not implementing it.

Managers, seeking to engender and strengthen innovative behaviors in engaged employees, should utilize 360-degree evaluation processes. Furthermore, the 360-degree evaluations should be designed to probe both tangible (technology and financial resource use) and intangible (idea generation and implementation) facets of innovation.

This study yields a deeper understanding of the relationship between engagement and innovative behaviors in the workplace along with managerial insights into the design and use of 360-degree evaluation.

The purpose of this research paper is to investigate the role of individual and cultural differences, specifically religious motivation and attitudes toward nepotism, in the selection of conflict management styles (obliging, avoiding, forcing, integrating and compromising), in the Middle-Eastern context.

The research surveyed a sample of 588 individuals (both Muslims and Christians), representative of the Jordanian population. Data were analyzed through multiple ANOVAs and multiple regressions.

Results suggest that both religious motivation and attitude toward nepotism affect the choice of conflict management styles, while demographic variables, such as age and gender, do not seem to have an effect.

This paper constitutes one of the first attempts to investigate the conflict management style preferences of a Middle-Eastern society and the role of two important cultural variables, namely, religious motivation and attitudes toward nepotism, which have not been previously investigated by conflict management research.

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 purpose of this paper is to present insights regarding the barriers that prevent women in Lebanon reaching parity with men in senior leadership positions. The paper also portrays men and women’s varying perceptions regarding these barriers.

A total of 129 participants at a Lebanese university took part in the study. The data collected were analyzed using SPSS. Frequencies and χ2-tests were conducted.

The findings suggest that women are more likely to be discriminated against and are thus more likely to be underrepresented in top leadership positions. Organizational and cultural barriers were considered to cause this discrimination. Women were more likely than men to believe that women face more barriers while climbing the career ladder. Men were more likely than women to believe that organizations are the parties responsible for this underrepresentation, more so than the surrounding culture. Surprisingly, a sound proportion of women believed that men are more competent at occupying top management positions in Lebanon.

This is one of the few studies to explore Lebanese perceptions on the workplace’s glass ceiling. Further, it examines the differences in opinions between males and females on women in the workplace, which has not been previously studied. This research contributes further to the existing body of knowledge on women in management in Lebanon and the Middle Eastern region, which is generally small in quantity.