Engineering Management
Permanent URI for this collection
Browse
Recent Submissions
Now showing 1 - 5 of 170
- ItemFACTORS INFLUENCING THE ADOPTION OF ARTIFICIAL INTELLIGENCE TOOLS IN PALESTINIAN HEALTHCARE SECTOR: AN EMPIRICAL STUDY(An-Najah National University, 2025-08-26) Abdullah, Nour Eddine Adeeb MuhammadRecent years have witnessed rapid growth in the application of artificial intelligence (AI) in the healthcare sector. However, some developing countries, such as Palestine, have not seen significant interest in this field. This study aims to explore the key factors and barriers affecting the adoption of AI technologies in the Palestinian healthcare sector, focusing on the levels of trust and ethical concerns faced by healthcare workers. The Technology Acceptance Model (TAM) was adopted as the primary framework for explaining behaviors, given its ability to analyze the impact of perceived ease of use (PE) and perceived usefulness (PU) on intentions to use. To gain a deeper understanding of technology adoption behavior, a mixed-methods approach was adopted, combining qualitative and quantitative methods (Venkatesh et al., 2016). The qualitative phase included semi-structured interviews with a group of physicians and healthcare professionals. The transcripts were analyzed using NVivo 14 software, employing coding and thematic analysis to identify key themes related to awareness, biases, and ethical barriers. The quantitative phase used a structured questionnaire distributed to a random sample of 186 participants from Palestinian hospitals, clinics, and healthcare institutions. The questionnaire was designed based on validated and reliable measures, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results showed that AI adoption is primarily influenced by organizational and ethical factors. In enhancing overall performance through PE, institutional pressure (IP), legal compliance, and ethical concern (EA) played a significant role, while financial readiness (FR) and top management support (TMS) had no significant impact. The results indicate that the availability of resources or management support, while important, are not sufficient on their own to boost trust or improve adoption intentions. The study also revealed that practical experience, quality of training, and external incentives play a crucial role in shaping healthcare professionals' perceptions of AI systems. This study helps bridge the knowledge gap by examining the Palestinian reality, which faces resource and institutional challenges and is unique in this regard. It offers practical insights for enhancing self-awareness, reducing biases, and improving ethical decision-making regarding AI applications in the healthcare sector. Its findings offer valuable recommendations for policymakers, clinicians, and technology developers on how to accelerate the adoption of these technologies and optimize their use in similar resource-limited settings.
- ItemTHE IMPACT OF TOTAL QUALITY MANAGEMENT ON PROJECT PERFORMANCE: THE MEDIATING ROLE OF ORGANIZATIONAL WILLINGNESS FOR ARTIFICIAL INTELLIGENCE IN THE AEC SECTOR IN PALESTINE(An-Najah National University, 2025-09-02) Rommaneh, Al HarethThis research explores the relationship between the Total Quality Management (TQM) and the performance of projects in the architectural, engineering, and construction (AEC) companies in Palestine, focusing on the mediating role of the organizational willingness in adopting Artificial Intelligence (AI). Although TQM has been linked for a long time with efficiency and competitiveness, research on the intersections of TQM and new technologies is currently understudied, particularly in fragile economies like Palestine. The research problem comes from the steady challenge of the Palestinian AEC firms in providing high quality results under conditions of limited resources, political uncertainty, and pressure to stay competitive. To fill this gap, the study was initiated as a mixed-method design. A structured questionnaire was distributed to 120 respondents from AEC firms and the data were analyzed using a statistical analysis method called Structural Equation Modeling (Smart-PLS). In addition, semi-structured interviews with managers and practitioners were conducted to complement and place the quantitative results in context. The results show that the TQM practices have a significant effect in project performance, both directly and indirectly in terms of organizational willingness to adopt AI. The addition of the "results" dimension to TQM was found to be useful in strengthening the explanation of both performance outcomes, thus tying quality practices with measurable indicators of success. Theoretically, the research contributes to the application of the Resource-Based View (RBV) and Contingency Theory through the demonstration of an interaction between internal quality capabilities and external pressures to shape AI readiness and, finally, performance. Practically, it serves as a guide to Palestinian AEC firms and policy makers looking to boost resilience and competitiveness. The recommendations point out the need for embedding quality principles and building readiness for digital transformation, providing a pathway for achieving better project results in a challenging environment.
- ItemDIGITAL TRANSFORMATION IN CONSTRUCTION MANAGEMENT: ASSESSING THE READINESS OF PALESTINIAN COMPANIES(An-Najah National University, 2025-06-17) Qabajah, AzmiThis study investigates the readiness of Palestinian construction companies to adopt digital transformation (DT) using artificial intelligence (AI) tools, while identifying associated challenges and proposing strategic solutions. In light of low productivity and marginal profit margins in the construction sector, DT is seen as a driver for improving project performance and innovation. The study evaluates how strategy, technological infrastructure, and human resources affect DT adoption and examines digital maturity as a mediating factor. A mixed-method approach was adopted. Qualitative data were collected through 13 semi-structured interviews, while quantitative data were obtained via a structured questionnaire distributed to 333 companies, with 143 valid responses (response rate: 42.9%). The Partial Least Squares Structural Equation Modeling (PLS-SEM) technique was used for data analysis. The findings reveal that the level of digital transformation adoption (ADT) was high (mean = 3.73/5), digital maturity (DM) scored a mean of 3.64, while project performance (MP) showed a very high level (mean = 4.18). Among ADT dimensions, technology had the highest influence (mean = 3.96), followed by strategy and human resources (mean = 3.62 each). The structural model showed strong, significant relationships between DT adoption and project performance (R² = 0.712), with digital maturity partially mediating this relationship (VAF = 52%). Key challenges identified include weak digital skills, limited infrastructure, and regulatory constraints. In response, the study proposes a strategic framework that includes: (1) investment in modern digital infrastructure, (2) development of digital competencies, and (3) regulatory reform. These strategies aim to enhance digital adoption and ensure sustainable performance gains in the Palestinian construction sector. This research provides empirical evidence of DT readiness and contributes actionable solutions and policy recommendations to accelerate digitalization in developing construction markets.
- ItemSUSTAINABLE SOLID WASTE MANAGEMENT VEHICLE ROUTING PROBLEM CONSIDERING DRIVERS HEALTH STATE AND RISK OF ACCIDENTS(An-Najah National University, 2024-03-04) Snouber, AbedalazizDue to the rapid growth of urbanization, the issue of solid waste management has drawn the attention of society and all stakeholders, because of the harm that will affect citizens and the environment if waste is not managed properly. Our research aims at solving a solid waste management vehicle routing problem that integrates the three pillars of sustainability; environmental, economic, and social. More specifically, our approach intends to investigate the effect of different drivers’ health state on the different parameters in solid waste management networks, by estimating the probability of suffering from work-related injuries, using Markov’s Chain model. In addition, our approach extends the reality of the model by considering different parameters and variables that will improve its practicality, such as including different cost functions. Furthermore, to ensure sustainable business practices, our model aims at minimizing the CO2 emissions resulting from different types of waste vehicles. Also, the social factor was studied by considering drivers’ health condition, minimizing the risk of accidents facing drivers, and minimizing any deviation from balanced workload between drivers. The Non-dominated Sorting Genetic Algorithm (NSGA) was used to solve the developed model, due to its ability to tackle multi-objective vehicle routing problems in general, and Solid Waste Management Vehicle Routing Problems in particular. After solving the proposed model, results revealed the effect of driver’s health states on different cost functions, in addition to the negative impact of high travel distance and waste vehicle load on the health condition of drivers. Sensitivity analyses illustrated how different model variables and parameters interact with each other, in addition to the effect of travel distance and vehicle load on drivers’ health conditions. The execution of this model in the waste management sector yields many advantages for service providers, due to its ability to monitor the health condition of drivers at each node in the network. This results in productive healthy drivers carrying out operations, who can achieve financial success along with a healthy and safe working environment.
- ItemA FRAMEWORK STRATEGY FOR SUSTAINABILITY CONSTRUCTION WASTE MANAGEMENT: CASE OF WEST BANK, PALESTINE(An-Najah National University, 2024-04-06) Hareez, FirasThis study aims to develop a strategic framework for sustainable construction and demolition (C&D) waste management in the West Bank of Palestine. Currently, no regulatory system governs C&D waste, resulting in unsustainable practices like dumping and burning that degrade the environment and public health. Previous research provided initial estimates of waste quantities, but gaps remain regarding generation patterns, stakeholder roles, and barriers. The research uses a mixed-methods approach, including questionnaires with 100 professionals and interviews with 10 interviewees. Secondary data from literature and reports supplements the Analysis. Findings show a lack of on-site segregation and essential management, 35% of the debris was dumped and more than 5% of the debris was burned illegally. Joint Service Councils manage collection and disposal but have limited capacity and funding. Political fragmentation also complicates coordination. Significant barriers include inadequate policies, infrastructure, lack of private sector compliance, and socioeconomic pressures. Study proposes a strategic framework to address these challenges to establish a coordinated C&D waste governance system by 2027. Objectives focus on strengthening regulations, improving on-site practices, developing infrastructure networks, boosting reuse/recycling markets, and creating sustainable financing mechanisms. A phased implementation plan outlines priority actions, responsibilities, and timelines for stakeholders to transition the sector toward sustainability. The framework provides a roadmap to guide reforms and capacity building needed to manage C&D waste responsibly in the West Bank.