This study investigates the impact of green innovation strategy on project management performance in the food sector of Saudi Arabia, examining the mediating roles of strategic quality planning and strategic leadership. Using a cross-sectional quantitative approach, data were collected in January 2025 from 341 employees through a convenience sampling technique. Structural equation modeling via SmartPLS was employed to analyze the data. Results indicate that green innovation strategy positively influences strategic quality planning (β = 0.655) and strategic leadership (β = 0.541), which in turn significantly enhance project management performance (β = 0.566 and β = 0.657, respectively). Additionally, strategic quality planning (β = 0.456) and strategic leadership (β = 0.505) partially mediate the relationship between green innovation strategy and project management performance. These findings highlight the critical role of green innovation and strategic management practices in improving project outcomes within Saudi Arabia’s food industry.

All projects require a structure to meet project requirements and achieve established goals. This framework is called project management. Therefore, project management plays an important role in national development and economic growth. Project management includes various knowledge areas such as project integration management, project scope management, project schedule management, etc. The article focuses on the resource-constrained project scheduling known as problem so- called the resource-constrained project scheduling problem (RCPSP). The RCPSP is a part of schedule management. The standard RCPSP has two important constraints, resource constraints and precedence relationships of activities during project scheduling. The objective of the problem is to optimize and minimize the project duration, subject to the above constraints. In this paper, we develop a convolutional neural network approach to solve the standard single mode RCPSP. The advantage of this algorithm over conventional methods such as metaheuristics is that it does not need to generate many solutions or populations. In this paper, the serial schedule generation scheme (SSGS) is used to schedule the project activities using an evolved convolutional neural network (CNN) as a tool to select an appropriate priority rule to filter out a candidate activity. The evolved CNN learns according to the eight project parameters, namely network complexity, resource factor, resource strength, average work per activity, etc. The above parameters are the inputs of the network and are recalculated at each step of the project planning. Moreover, the developed network has priority rules which are the outputs of the developed neural network. Therefore, after the learning process, the network can automatically select an appropriate priority rule to filter an activity from the eligible activities. In this way, the algorithm is able to schedule all project activities according to the given project constraints. Finally, the performance of the Convolutional Neural Network (CNN) approach is investigated using standard benchmark problems from PSPLIB in comparison to the MLFNN approach and standard metaheuristics.

Project management has a fundamental role in national development, industrial development, and economic growth. Schedule management is also one of the knowledge areas of project management, which includes the processes employed to manage the timely completion of the project. This paper deals with the Resource-Constrained Project Scheduling Problem (RCPSP), which is a part of schedule management. The objective of the problem is to optimize and minimize the project duration while constraining the resource quantities during project scheduling. There are two important constraints in this problem, namely resource constraints and precedence relationships of activities during project scheduling. Many methods such as exact, heuristic, and meta-heuristic have been developed by researchers to solve the problem, but there is a lack of investigation of the problem using methods such as neural networks and machine learning. In this article, we develop a multi-layer feed-forward neural network (MLFNN) to solve the standard single- mode RCPSP. The advantage of this method over evolutionary methods or metaheuristics is that it is not necessary to generate numerous solutions or populations. The developed MLFNN learns based on eight project parameters, namely network complexity, resource factor, resource strength, average work per activity, percentage of remaining work, etc., which are calculated at each step of project scheduling, and identified priority rules, which are the outputs of the developed neural network. Therefore, after the learning process, the network can automatically select an appropriate priority rule to filter out an unscheduled activity from the list of eligible activities and schedule all activities of the project according to the given project constraints. Finally, we investigate the performance of the presented approach using the standard benchmark problems from PSPLIB.

Cybersecurity threats have become a structural risk to digital project management, challenging not only digital data integrity but also long-term organizational sustainability. While prior research has emphasized awareness and technical safeguards, limited attention has been given to the behavioral–cognitive mechanisms through which cybersecurity knowledge translates into sustainable organizational outcomes. Drawing on Protection Motivation Theory and the Theory of Planned Behavior, this study examines the moderated-moderation effect of Perceived Risk (PR) and Risk of Behavior (RB) on the relationship between Cybersecurity Knowledge of Threats (CKT) and Organizational Sustainability (OS). Using survey data collected from 235 project management staff across UK organizations, the results of structural equation modeling reveal a significant three-way interaction (CKT × PR × RB). The findings indicate that CKT enhances OS most strongly when both PR and RB are high, suggesting that knowledge translates into sustainability only when employees accurately perceive cyber threats and respond with appropriate protective actions. This joint amplification effect uncovers a previously underexplored mechanism linking individual-level cognition to macro-level organizational resilience.

This study's objective is to analyze the factors that influence whether or not small and medium-sized enterprises (SMEs) use business intelligence. Based on an exhaustive assessment of the literature, the study offers a model dependent on the diffusion of innovation and augmented with factors expressing the idea of project management maturity (PMM). The research applied structural equation modelling (SEM) to examine data obtained from 112 Jordanian company workers. The findings showed that the adoption of business intelligence has a positive and significant relationship to the complexity, compatibility, and relative advantage of business intelligence; the level of project management maturity has a significant effect on the level of relative advantage, compatibility, and complexity; and the level of project management maturity is significantly associated with the change management and knowledge sharing practices in SMEs. However, we contend that further study has to be carried out, particularly in the context of developing nations, in order to get a comprehensive understanding of how different SMEs may effectively deploy and make use of business intelligence.

This study uses the PMI® framework as a reference to analyse the impact of Project Management (PM) competencies on organisational competitiveness and productivity in southwestern Colombia. The research evaluates three key dimensions: Organisational Practices in PM (PMP), Skills, Attitudes and Values (HABI) and their influence on Business Competitiveness (COMPE) and Productivity and Innovation Indicators (PROD). A survey was conducted with 221 CESMAG University Project Management Postgraduate Programme graduates (2016–2023). Data were collected using Likert-type scales and analysed using structural equation modelling (PLS-SEM) to ensure the reliability and validity of the constructs. The results confirm that both organisational practices and individual competencies significantly enhance competitiveness and productivity. PMP was found to have a positive effect on strategic performance indicators, while HABI was found to have an even stronger influence on innovation and value creation. These findings emphasise the strategic importance of postgraduate training in project management (PM) for regional development. Beyond academic contributions, the study provides actionable insights for businesses, universities and policymakers, demonstrating how strengthening PM competencies can foster innovation, operational efficiency and sustainable competitiveness in emerging economies.

Firms operating in emerging markets deal with volatile and uncertain conditions that force them to continuously adapt and reconfigure their resources. We use the Dynamic Capabilities View as our theoretical lens to investigate how dynamic capabilities work together with digital readiness to affect performance in SMEs that face these turbulent environments. Dynamic capabilities give managers the means to sense changes in their environment, seize new opportunities when they arise, and realign organizational resources as needed. Digital readiness provides the technological infrastructure required to make these strategic and project-level adjustments work in practice. We gathered survey data from 305 food-processing SMEs in Jordan and analyzed the data using Partial Least Squares Structural Equation Modelling. Our results show that dynamic capabilities have a strong positive effect on firm performance. We also found that digital readiness amplifies this effect in important ways. The study contributes to strategic management, operations management, and project management research. It demonstrates that building capabilities while aligning digital tools helps firms navigate environmental uncertainty more effectively. For managers, the findings highlight something important: developing both organizational agility and digital infrastructure can turn turbulent market conditions into competitive advantages. The results offer practical guidance for operations and project managers in SMEs who are working to execute sustainability-oriented operational projects. They show that capability development paired with digital preparedness supports smoother execution and leads to stronger project outcomes.

The purpose of this paper is to present the relief operations (RO), responding to a sudden, natural, national disaster (SNND) as a multi-mode resource-constrain multi-project scheduling problem (MRCMPSP). A conceptual framework at a strategic level is constructed and the Colombian RO for an earthquake response is shown as an illustrative case. We concluded that RO can be addressed as a MRCMPSP and that for Colombian case, it is a convenient way to board it. Addressing RO as a MRCMPSP allows managers to implement different project scheduling tools successful in other contexts.

There is abundant literature on sustainable construction projects. This review study collects a set of studies to understand the depth of the topic as per the Sustainable Development Goals (SDGs). For this purpose, the Scopus database is explored with a systematic review approach, and 80 studies are selected. The literature emphasizes the integration of human capital, technological innovation, governance, and financial support to achieve sustainable objectives in construction projects. Moreover, education can improve technical and strategic competencies in graduates to promote experiential learning for the construction industry. Furthermore, sustainable construction can be enhanced by circular economy principles. In addition, risk management also needs attention to ensure operational reliability in construction projects. For this purpose, institutions and governance can align technical and ecological priorities in a project to achieve sustainability objectives. Innovations can also improve efficiency and knowledge management. Lastly, economic and financial mechanisms can also support this phenomenon. The study suggests promoting education, technology, and governance to support sustainable construction as per the SDGs.

Project management and corporate strategic responses can play active roles in Corporate Environmental and Sustainability Performance (CESP) in times of Economic Policy Uncertainty (EPU) as per Sustainable Development Goals (SDGs). The current literature is missing a review of such linkages. Thus, this review article contributes to the literature by critically evaluating the literature on the complex connection between EPU and CESP, focusing on the concepts of green innovation, Environmental, Social, and Governance (ESG) outcomes, and project management strategies. Following a comprehensive systematic review approach, this article selects 76 empirical studies across developed, underdeveloped, and emerging markets. The findings disclose that EPU was carrying a mixed effect with both a barrier and a potential driver of sustainability initiatives at the firm level. Thus, the increasing EPU reduces long-term green investments, disrupts energy transitions, increases emissions, and increases environmental risk exposure on the one hand. On the other hand, it also promotes project management, strategic adaptation, innovation, and Corporate Social Responsibility (CSR) among firms with strong governance structures and digital capabilities. Moreover, board diversity, CSR disclosure quality, institutional strength, media attention, and technological transformation played their moderating role in determining the effect of EPU on CESP. Furthermore, sectoral heterogeneity and regional asymmetries were also found to be responsible for determining the relationship between EPU and CESP. These findings would guide the policy implications for investors and corporate leaders aiming to enhance CESP under the volatile EPU.