Throughout the course of a project cycle, the many phases of project management—including planning, execution, control and monitoring, and ending—are integrated and executed. In modern firms, project management has become the dominant tool for managing change. Best practices have emerged due to global project management practices and company evolution. The primary goal was to investigate how project management approaches affected project performance of the Saudi Arabia Small and Medium Sized Enterprises (SMEs). This study investigated the impact of various project management practices including risk management, communication, leadership, and stakeholder management, on project performance in manufacturing SMEs in Riyadh, Saudi Arabia. A quantitative research methodology was employed, with data collected from 250 employees (i.e., supply chain, finance and R&D managers/supervisors) across 8 SMEs. The results revealed that risk management, leadership practices, and stakeholder management significantly contribute to project performance. Surprisingly, no significant relationship was found between communication practices and project performance. The findings of this study emphasize the importance of effective risk management, strong leadership, and efficient stakeholder management in achieving successful project outcomes. Finance managers and R&D managers in Saudi manufacturing SMEs should lead and engage stakeholders to improve project performance. Supply chain managers must manage risk and maintain stakeholder relationships to avoid disruptions. Communication improvements, despite their small impact, are essential for departmental coordination. Global project management strategies tailored to local culture and business will improve project success.
This research aims to empirically examine the role of learning organization practices in enhancing sustainable organizational performance, utilizing knowledge management and innovation capability as mediating variables. The study was conducted in public IT companies across China, which is a vital sector for driving innovation and economic growth. A mixed-methods approach was employed, with quantitative methods accounting for 70% and qualitative methods for 30% of the research. Purposive sampling was utilized to distribute questionnaires to 546 employees from 10 public IT companies. Statistical analysis was conducted using Structural Equation Modeling (SEM). The findings indicate that learning organization practices significantly influence knowledge management practices (β = 0.785, p < 0.001) and innovation capability (β = 0.405, p < 0.001). Furthermore, knowledge management practices positively contribute to sustainable organizational performance (β = 0.541, p < 0.001), while innovation capability also has a positive effect (β = 0.143, p < 0.001). Moreover, knowledge management practices partially mediate the relationship between learning organization practices and sustainable performance, with a total effect of 0.788 (p < 0.001). The mediating role of innovation capability is also significant, with a total effect of 0.422 (p = 0.045). The study further includes qualitative in-depth interviews with 20 managers from 10 IT companies across five regions in China: East, South, West, North, and Central. Senior managers were selected through a stratified sampling method to ensure comprehensive representation by including both the largest and smallest companies in each region. These findings underscore the critical role of learning organizations in promoting sustainability through effective knowledge management and innovation capabilities within the IT sector.
This study explores the complex dynamics of handling augmented reality (AR) data in higher education in the United Arab Emirates (UAE). Although there is a growing interest in incorporating augmented reality (AR) to improve learning experiences, there are still issues in efficiently managing the data produced by these apps. This study attempts to understand the elements that affect AR data management by examining the relationship between the investigated variables: faculty readiness, technological limits, financial constraint, and student engagement on data management in higher education institutions in the UAE, building on earlier research that has identified these problems. The research analyzes financial constraints, technological infrastructure, and faculty preparation to understand their impact on AR data management. The study collected detailed empirical data on AR data management in UAE higher education environments using a quantitative research methods approach, surveys. The reasons for choosing this research method include cost-effectiveness, flexibility in questionnaire design, anonymity and confidentiality involved in the chosen methods. The results of this study are expected to enhance academic discourse by highlighting the obstacles and remedies to improving the efficiency of AR technology data management at higher education institutions. The findings are expected to enlighten decision-making in higher education institutions on maximizing AR technology’s benefits for improved learning outcomes.
Introduction: The digital era has ushered in transformative changes across industries, with the real estate sector being a pivotal focus. In Guangdong Province, China, real estate enterprises are at the forefront of this digital revolution, navigating the complexities of technological integration and market adaptation. This study delves into the intricacies of digital transformation and its profound implications for the financial performance of these enterprises. The rapid evolution of digital technologies necessitates examining how such advancements redefine operational strategies and financial outcomes within the real estate landscape. The inclusion of government support as a variable in our study is deliberate and stems from its profound influence on shaping the digital landscape. Government policies and initiatives provide a regulatory framework and offer strategic direction and financial incentives that catalyze digital adoption and integration within the real estate sector. By examining the moderating effect of government support, this study aims to uncover the nuanced interplay between policy-driven environments and the financial performance of enterprises undergoing digital transformation. This exploration is essential to understanding the broader implications of public policy on private-sector innovation and growth. Objectives: The primary objective of this research is to evaluate the impact of digital transformation on the financial performance of Guangdong’s real estate enterprises, with a specific focus on return on equity (ROE) and return on assets (ROA). Additionally, this study aims to scrutinize the role of government support as a potential moderator in the relationship between digital transformation and financial success. The research seeks to provide actionable insights for policymakers and industry players by understanding these dynamics. The digital transformation of Guangdong’s real estate sector presents a complex landscape of challenges and opportunities that shape the industry’s evolution. On one hand, the integration of innovative digital technologies into established operational frameworks poses significant challenges. These include the need for substantial investment in new infrastructure, the imperative for a cultural shift towards digital literacy across the workforce, and the continuous demand for upskilling to remain agile in an increasingly digital market. On the other hand, digital transformation affords manifold opportunities. For instance, enhanced operational efficiencies through automation and data analytics offer substantial benefits in terms of cost savings and process optimization. Furthermore, leveraging data-driven insights enables more informed strategic decision-making, which is critical in a competitive real estate market. The capacity to innovate service offerings by tapping into digital platforms and customer relationship management systems also presents a significant opportunity for real estate enterprises to differentiate themselves and capture new market segments. Methods: This study explores the digital transformation of real estate firms in Guangdong, highlighting government support as a critical moderator. Findings show that digital initiatives improve company performance, with government backing amplifying these benefits. Regional disparities in support suggest a need for tailored strategies, indicating the importance of policy in driving digital adoption and innovation in the sector. The study advises firms to leverage local policies and policymakers to address regional imbalances for equitable digital transformation. This study uses a sample of 28 real estate enterprises in Guangdong Province from 2012 to 2022. Panel data analysis with a fixed effects model tests the hypotheses. The study also conducts robustness checks by replacing the key variables. Results: The findings indicate that digital transfo
We analyze Thailand’s projected 2023–2030 energy needs for power generation using a constructed linear programming model and scenario analysis in an attempt to find a formulation for sustainable electricity management. The objective function is modeled to minimize management costs; model constraints include the electricity production capacity of each energy source, imports of electricity and energy sources, storage choices, and customer demand. Future electricity demands are projected based on the trend most closely related to historical data. CO2 emissions from electricity generation are also investigated. Results show that to keep up with future electricity demands and ensure the country’s energy security, energy from all sources, excluding the use of storage systems, will be necessary under all scenario constraints.
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