Saudi Arabia is increasing renewable energy generation, electrifying its systems and implementing digital technologies in the grid, all against a backdrop of a climate in which summer temperatures, dust, humidity and other co-occurring environmental stresses simultaneously raise demand and degrade the electricity infrastructure. This study synthesizes the evidence published between 2020 and 2025 to examine how climate-resilient smart-grid planning can help reduce these interconnected risks. A structured integrative review was carried out by selecting a purposeful collection of peer-reviewed studies and official energy and climate reports, with a focus on Saudi Arabia, the Gulf Cooperation Council, arid power systems, and methods of resistance that can be transferred to other contexts. The evidence was analysed along four dimensions: hazard, exposure, vulnerability, and adaptive capacity, and then linked to the areas of generation, transmission, distribution, demand, storage, digital control, and governance. The synthesis reveals that extreme heat is not simply a single issue relating to equipment; it causes cooling peaks at the same time, reduces both generation and network capacity, accelerates thermal ageing, and can occur alongside photovoltaic soiling, constraints on water use, and communication or cyber-physical failures. The most effective approach to planning therefore involves a multi-layered system that incorporates climate-based load forecasting, dynamic asset ratings, heat-resistant equipment, a varied geographical mix of renewable energy sources, storage, demand response, microgrids for critical loads, advanced metering, artificial intelligence, and regional interconnection. The review suggests a planning framework specific to Saudi Arabia that takes into account resilience together with cost and decarbonisation, using measures such as critical-load continuity, energy not served, restoration time, thermal headroom, and forecast error in severe situations. It finds that climate resilience should be integrated into long-term capacity expansion, grid codes, asset standards and operational digital twins, rather than an add-on for emergency management.
Government and enterprise applications increasingly depend on cloud platforms for elasticity, rapid service delivery, analytics and digital integration, yet mission-critical workloads cannot be optimized through a simple public-cloud-first migration. They require deliberate placement across private, public, sovereign and on-premise environments according to service-level objectives, data sensitivity, latency, dependency and recovery requirements. This review examines how hybrid cloud architecture can be optimized for mission-critical applications in Saudi Arabia. It synthesizes literature on multi-cloud orchestration, workload portability, containerized resource management, observability, cybersecurity and resilience, and interprets these findings against Saudi Cloud First policy, Digital Government Authority guidance, Communications, Space and Technology Commission regulations, National Cybersecurity Authority controls and Vision 2030 priorities. The analysis finds that hybrid cloud value depends less on the number of connected platforms than on unified policy, application-aware placement, automated orchestration, end-to-end observability and tested continuity. A Saudi-oriented reference model is proposed in which governance and data classification drive placement decisions, while cloud-native portability, automation and resilience controls sustain service continuity. The review concludes that hybrid cloud can support Vision 2030 digital-government and enterprise goals when architecture is treated as a governed operating model rather than a collection of disconnected infrastructures.
Mohammad Younus
Glob Acad J Econ Buss; 2026, 8(5): 1087-1098
DOI : https://doi.org/10.36348/gajeb.2026.v08i05.003
The vast number of projects carried out by Saudi Arabia involve a great deal of construction, a wide range of different kinds of buildings, modern building services, and very strict deadlines for completion. Under these circumstances, fire safety resilience depends not only on the design complying with the relevant codes but also on the systems installed being clearly complete, capable of working together, and able to be restored before the projects are handed over. This study treats inspection, testing and commissioning (ITC) as a continuous process for making sure that the fire protection and life-safety systems work in Saudi giga-projects. A structured and integrative review was carried out in accordance with the PRISMA 2020 reporting guidelines and included peer-reviewed studies, standards and Saudi policy documents published between 2020 and 2025. The evidence was divided into five themes: the quality of inspection, the functional testing of subsystems, integrated system testing, digital verification and lifecycle governance. The review shows that resilience is reduced when verification is left to the individual contractors, when the documentation is fragmented, when interface tests are delayed, or when acceptance is based on the activation of components rather than on the system's performance in a given scenario. On the other hand, risk-based inspection, functional testing that is witnessed, integrated sequences covering alarm systems, smoke control, emergency power and egress systems, and digitally traceable evidence all increase the likelihood that the safety functions will operate if a real fire takes place. Even though digital twins, IoT sensing, computer vision and BIM can improve traceability and situational awareness, they do not substitute for competent inspection or independent witnessing. The paper presents a seven-stage Fire Safety Resilience Assurance Framework which is in line with the Saudi Fire Protection Code and with current NFPA commissioning practices. The framework unites the design intent, the verification of installation, pre-functional checks, functional tests, integrated scenarios, handover evidence and periodic retesting. It provides owners, regulatory authorities, commissioning teams and contractors with a flexible approach for reducing latent defects and for guaranteeing operational dependability in the context of complex Vision 2030 developments.
Mohammed Juned Nijami
Glob Acad J Econ Buss; 2026, 8(5): 1099-1110
DOI : https://doi.org/10.36348/gajeb.2026.v08i05.004
At present, intelligent oil and gas facilities are using safety instrumented systems (SIS), distributed control systems (DCS), connected field instrumentation, historians, edge computing, and advanced analytics. Although the large amount of data generated can improve process safety, this benefit can only be achieved if the analytical integration still satisfies the required standards concerning independence, determinism, and assurance for safety functions. This article looks at how the SIS, the DCS, and the real-time instrumentation analytics can be combined so as to establish an evidence architecture that helps in the early detection of abnormal conditions, the evaluation of barrier health, the contextuation of alarms, and the provision of risk-informed support for human decision-making. A structured integrative review has been carried out in line with the PRISMA 2020 and PRISMA-S reporting guidelines in order to summarise the peer-reviewed and credible literature published between 2020 and 2025. The evidence is divided into five areas: functional-safety architecture, control and alarm management, instrumentation data quality, fault diagnosis and dynamic risk analytics, and cyber-human assurance. The synthesis shows that the most defensible design is not one in which the analytics control the SIS, but rather a layered architecture in which both the SIS and the DCS keep their present operational roles while authenticated, time-aligned, read-only data are sent to an independent analytics environment. This setup allows for predictive and contextual insights absent creating an unverified actuation path into the protection layers. The paper suggests an assured integration architecture and a five-level implementation maturity model. It concludes that the future value for process safety will depend less on the novelty of the algorithms themselves and more on traceable measurements, validated models, secure interfaces, explainable outputs, disciplined management of change, and clear human authority over safety-critical decisions.
Khaleel Anwar Ali Khan
Glob Acad J Econ Buss; 2026, 8(5): 1111-1123
DOI : https://doi.org/10.36348/gajeb.2026.v08i05.005
The health sector's programme for transformation in Saudi Arabia needs a medical supplies system which can provide the correct product, in the right condition, at the right place, together with reliable information concerning cost and traceability. This study looks at enterprise resource planning as the core element for improving procurement, inventory management, warehousing, distribution, supplier management, and financial control within the Kingdom's healthcare and medical supplies sector. A structured integrative review of 30 sources published between 2020 and 2025 was carried out, with a focus on peer-reviewed literature relating to healthcare supply chains, ERP systems, digital transformation, resilience, analytics, and the Saudi health system, as well as on official Vision 2030 and Ministry of Health documents. The findings show that the value of ERP is mainly derived not from the installation of software but from standardised master data, end-to-end workflows, interoperable interfaces, well-disciplined inventory policies, and timely analytics. It also appears that artificial intelligence, the Internet of Things, blockchain, and business analytics generate greater operational value when they are linked to a stable ERP system rather than when they are introduced as separate applications. For Saudi Arabia, the most important fields for improvement are integrated demand planning, visibility into supplier performance, control of batches and expiry dates, automated replenishment, readiness for recalls, and transparency of spending across both central and provider-level networks. The review suggests a framework for optimisation that is aligned with Vision 2030 and links ERP capabilities to process mechanisms, measurable supply outcomes, and the objectives of the healthcare system. It concludes that a transformation centred on ERP can improve availability, spending efficiency, resilience, localisation, and governance, provided that the implementation is supported by data governance, interoperability standards, workforce development, cybersecurity, and continuous performance management.
Saudi Arabia’s electronic invoicing programme has converted tax invoicing from a document-generation task into a regulated, API-mediated financial process. For enterprises running Oracle ERP, compliance therefore depends on more than producing a valid invoice: data must be transformed into the prescribed XML structure, validated against business rules, secured with approved credentials, submitted to the FATOORA platform within the applicable clearance or reporting model, reconciled with the ERP ledger, and retained with auditable evidence. This review examines how a cloud-native architecture can integrate Oracle ERP, ZATCA interfaces and automated financial controls while supporting the Kingdom’s wider digital transformation agenda. Evidence published between 2020 and 2025 is synthesised across electronic invoicing, cloud ERP, API security, continuous auditing, digital tax administration and Saudi regulatory guidance. The review develops an architecture organised around transaction capture, canonical data mapping, validation, security, API orchestration, response handling, immutable evidence, reconciliation and control monitoring. It argues that compliance reliability is improved when ZATCA rules are treated as executable control requirements rather than downstream reporting checks. The proposed model separates enterprise accounting logic from regulatory integration, supports resilient retries without duplicate submission, and creates traceable links between source transactions, signed XML, platform responses and accounting entries. The paper concludes that cloud-native integration can strengthen compliance, scalability and auditability, but only where enterprises govern master data, credentials, exception handling, segregation of duties and change management as tightly as the integration code itself.
Advanced manufacturing in Saudi Arabia is moving from capacity expansion toward digitally enabled productivity, reliability, localization, and resource efficiency. This review examines how four complementary mechanisms—predictive maintenance, Overall Equipment Effectiveness (OEE), digital twins, and Lean Six Sigma—can be integrated to optimize advanced manufacturing machinery under the industrial priorities of Saudi Vision 2030. A structured integrative review of literature published from 2020 to 2025 was undertaken across smart manufacturing, maintenance engineering, production performance, digital-twin applications, and operational excellence, with Saudi industrial strategy documents used to contextualize implementation. The synthesis shows that predictive maintenance improves failure anticipation but requires disciplined data quality and maintenance workflows; OEE converts equipment losses into an operational performance language but can mislead when treated as an isolated utilization target; digital twins create a dynamic decision layer linking physical assets with simulation and prognostics; and Lean Six Sigma converts diagnostic insight into controlled, repeatable improvement. Their greatest value therefore emerges through integration rather than parallel deployment. The paper develops a closed-loop reliability-performance framework and a staged maturity roadmap for Saudi factories, emphasizing brownfield connectivity, criticality-based sensing, interoperable data architecture, workforce capability, cybersecurity, and value-based governance. The proposed approach supports higher asset availability, stable cycle performance, lower quality loss, and stronger local manufacturing capability while avoiding technology-led transformation without measurable operational return.
Enterprise business intelligence has traditionally depended on dashboards that visualize historical and near-real-time data for human interpretation. Although dashboards remain essential for transparency and performance monitoring, they often require decision makers to detect anomalies, interpret root causes, and translate insights into action. This paper proposes an agentic artificial intelligence framework for enterprise business intelligence modernization, shifting BI from passive reporting toward autonomous, governed, and decision-oriented intelligence. The study uses a conceptual design methodology supported by literature on agentic AI, enterprise analytics, decision intelligence, and national digital transformation priorities. The proposed framework integrates five layers: unified data foundation, semantic and KPI governance, agent orchestration, human-in-the-loop decision control, and performance assurance. It explains how AI agents can monitor business metrics, detect exceptions, generate contextual explanations, recommend actions, and support executive decision-making while preserving governance, accountability, and responsible AI controls. From a business and economic perspective, the framework links analytics modernization to productivity improvement, cost optimization, working-capital visibility, faster management response, and measurable return on AI investment. The framework is positioned for Saudi enterprises aligned with Vision 2030, where data and AI are central enablers of economic diversification, operational efficiency, and digital maturity. The paper contributes a practical modernization model for organizations seeking to evolve from descriptive dashboards to agentic intelligence ecosystems.
Saudi Arabia is enlarging its pharmaceutical and biotechnology base as part of a wider retreat from import dependence. For advanced drug-delivery products, however, adding capacity is not the same as adding capability. Performance in these products is governed by particle size, polymer microstructure, mixing history, sterile handling, device geometry, release kinetics and analytical control, and these variables prove stubbornly difficult to reproduce once a manufacturing site changes. This review examines how technology transfer and process scale-up must be combined if advanced drug-delivery manufacture is to take root in the Kingdom, covering modified-release oral products, hot-melt-extruded systems, lipid and polymeric nanoparticles, long-acting injectables, microneedle platforms and digitally manufactured dosage forms. A structured narrative method was used to assemble peer-reviewed evidence published between 2020 and 2025 together with the quality frameworks issued in that period. The Kingdom's starting position is quantified rather than asserted: analysis of the Saudi Food and Drug Authority formulary shows that 22.55% of registered items are manufactured domestically against 43.86% originating in Europe, that four producers account for 63% of domestic output, and that approximately 86% of surveyed national manufacturers cannot at present enable nanotechnology-based medicines even though more than 93% regard such products as important. Against this baseline the review argues that localization should be treated as a capability-transfer programme rather than an equipment-purchase exercise, requiring a product-specific knowledge package covering critical material attributes, critical process parameters, critical quality attributes, analytical procedures, process models and change-control logic. A phased pathway is proposed in which secondary operations and sterile fill-and-finish establish a learning base, followed by formulation ownership, platform manufacturing, advanced process control and regional export.
Muhammad Anas
Glob Acad J Econ Buss; 2026, 8(5): 1164-1172
DOI : https://doi.org/10.36348/gajeb.2026.v08i05.010
Saudi Arabia’s electricity system is undergoing a capital-intensive transition, in which efficiency improvements at existing and new generating assets must compete for funding with renewables, grids, storage, and gas infrastructure. This review explores how financing design is able to transform technically credible energy-efficiency opportunities in power generation into investable projects aligned with Vision 2030. Rather than viewing efficiency solely as an engineering issue, the paper integrates evidence on heat-rate improvement, combined-cycle optimisation, digital operation and maintenance, auxiliary-load reduction, flexible generation, energy-performance contracting, green bonds, sukuk, and blended finance. A structured review of peer-reviewed literature from 2020 to 2025 links technical savings to risk allocation, cash-flow certainty, and cost of capital. The findings show that financing quality significantly affects the bankability of efficiency projects, as verified savings are often distributed across fuel, maintenance, reliability, and capacity benefits rather than consolidated in a single revenue stream. In Saudi Arabia, the most compelling near-term approach is to aggregate repeatable efficiency measures across generation portfolios, apply transparent baselines and performance guarantees, and connect refinancing to verified outcomes. The review concludes that energy efficiency should be considered productive infrastructure: a financing category that can reduce system costs, support renewable integration, conserve fuels, and improve the credibility of transition investments under Vision 2030.
Saudi Arabia’s construction pipeline creates a practical resource-management challenge: project teams must reduce dependence on virgin aggregates and clinker-intensive products while controlling the quality, cost, durability and traceability risks associated with secondary materials. This review therefore moves beyond a general catalogue of recycled construction materials and develops a project-level implementation framework for Saudi building and infrastructure delivery. Thirty publications from 2020–2025 were synthesized around five decision stages: source identification, material qualification, application selection, procurement and approval, and site production control. Evidence on recycled concrete aggregate (RCA), reclaimed components, waste glass, plastics, steel slag, supplementary cementitious materials, geopolymer systems and recycled water is translated into practical acceptance gates for design, materials engineering, procurement, QA/QC and construction teams. The review shows that recycled content alone is a weak decision metric. For Saudi projects, the more defensible approach is to match the secondary material to a defined application and exposure class, verify source quality and contamination limits, validate trial mixtures or product performance, control moisture and batch variability, and document environmental and economic benefit at the functional-unit level. A role-based implementation matrix, stage-gate approval protocol and project KPI set are proposed to support real project execution under Vision 2030. The resulting framework is intended to help project teams convert circular-economy objectives into auditable material approvals, procurement decisions, inspection points and measurable resource-efficiency outcomes rather than treating recycling as a stand-alone sustainability claim.
Essam Ali Hassan Abdelaal
Glob Acad J Econ Buss; 2026, 8(5): 1185-1195
DOI : https://doi.org/10.36348/gajeb.2026.v08i05.012
Saudi Arabia's economic diversification and rapid digitalization have increased strategic risks linked to fragmented governance, risk management, and compliance. This integrative review examines how governance, risk, and compliance (GRC) can be structured as an organizational resilience capability within the Vision 2030 framework, rather than as separate control functions. The review synthesizes peer-reviewed research on enterprise risk management, corporate governance, compliance, digital transformation, cybersecurity, RegTech, and organizational resilience, focusing on evidence relevant to Saudi institutions and technology-intensive sectors. A transparent search and quality-assessment protocol prioritizes literature from 2020 to 2025, while retaining key foundational studies and a recent Saudi empirical anchor. The synthesis shows that resilience develops when governance defines decision rights and risk appetite, risk management translates uncertainty into prioritized action, compliance ensures reliable control behavior, and digital GRC enables timely, shared intelligence. These mechanisms strengthen anticipatory capacity, disruption absorption, adaptive coordination, recovery, and organizational renewal. However, integration may fail if GRC becomes overly centralized, metric-driven, technologically opaque, or disconnected from business ownership. Saudi evidence indicates that governance reform, ESG reporting, foreign investment, cyber governance, and digital transformation create mutually reinforcing pressures for integrated assurance. This paper presents a GRC-to-resilience framework and a four-stage maturity model for Saudi organizations. It concludes that resilience relies more on the integration of GRC into strategy, operations, data architecture, learning routines, and board oversight than on the mere existence of GRC functions. The review identifies research priorities including causal measurement, sector comparisons, AI-enabled GRC, regulatory interoperability, and resilience outcomes.
Saudi Arabia's capital market is moving from scale expansion toward deeper institutionalization, digital participation, and sophisticated trading infrastructure. Brokerage firms sit at a critical interface between investor intentions and exchange-level outcomes. This review examines how advanced decision analytics can improve brokerage operations while supporting liquidity, price discovery, resilience, and investor confidence under Vision 2030. A structured integrative review synthesized 30 peer-reviewed and institutional sources published from 2020 to 2025 across market microstructure, algorithmic and high-frequency trading, machine learning, reinforcement learning, financial risk analytics, securities regulation, and Saudi market development. Five analytics domains emerge: client and order intelligence, execution optimization, liquidity and market-making analytics, real-time risk and compliance, and operational resilience. Evidence indicates that analytics can reduce implementation shortfall, improve order routing and inventory control, and accelerate information incorporation into prices; however, benefits depend on market design, liquidity regimes, model governance, and automated participant behavior. Saudi evidence is timely because algorithmic and high-frequency traders now represent material shares of liquidity while market-making and post-trade infrastructure are expanding. The paper proposes a Saudi Brokerage Decision Analytics Framework linking governed data, predictive and prescriptive models, human oversight, execution controls, and market-quality metrics. Decision analytics should therefore be treated as a governed market capability whose success is measured jointly by brokerage efficiency and market integrity.
Cloud databases are now foundational to enterprise digital operations; however, their elasticity and distributed architecture increase the complexity of manual administration. This review investigates how artificial intelligence can facilitate bounded autonomy in cloud database management to enhance performance, reliability, and operational efficiency, with a specific focus on Saudi enterprises. A structured integrative review synthesizes peer-reviewed literature published primarily between 2020 and 2025, spanning database systems, cloud resource management, anomaly diagnosis, autonomous tuning, and Saudi cloud adoption. Learned query optimization and cardinality estimation improve execution decisions; reinforcement and Bayesian learning accelerate configuration tuning; workload-aware resource orchestration manages latency and utilization; and AI-supported monitoring reduces diagnosis and recovery cycles. Nevertheless, the literature reveals persistent limitations: model transfer across workloads is unreliable, optimization objectives are often narrower than enterprise service-level requirements, online exploration can introduce availability risks, and most evaluations are laboratory-based rather than longitudinal production studies. Saudi adoption studies further demonstrate that security, privacy, trust, and organizational readiness influence cloud decisions, indicating that technically advanced autonomy will not be adopted without auditable controls and clear accountability. Accordingly, this review proposes a closed-loop architecture in which telemetry, AI decision engines, policy constraints, database control actions, and human oversight function as a governed feedback system. The central conclusion is that autonomous cloud database management should be implemented as progressively delegated, observable, and reversible decision-making, rather than as unrestricted automation.
Top Editors
Dr. Sumathi Kumaraswamy
Associate Editorial Board
Assistant Professor Department of Economics and Finance College of Business Administration University of Bahrain Email: skumaraswamy@uob.edu.bh
Dr. Jitender Kumar
Associate Editorial Board
Assistant Professor, Department of Management Studies, Deenbandhu Chhotu Ram University Murthal, Sonepat, Haryana, India Email: jitenderkbatra@gmail.com
Omer Allagabo Omer Mustafa
Associate Editorial Board
Assistant Professor of Economics, Banking and Finance, Deputy Secretary of Academic Affairs-Sudan Academy for Banking and Financial Sciences (SABFS), Khartoum, Sudan E-mail: omergabo78@sabfs.edu.sd
Dr. Zahoor Ahmad Parray
Associate Editorial Board
Department of Management Studies, South Campus, University of Kashmir Anantnag, Jammu and Kashmir, India Email: zahoorhs@gmail.com
Dr. Hafnida Hasan
Associate Editorial Board
Assistant professor in Applied Sciences University (ASU), Kingdom of Bahrain Email: hafnida.hasan@asu.edu.bh
Dr. Ulysses J Brown III
Associate Editorial Board
College of Business Savannah State University 3219 College Street Savannah GA 31404 Email: brownu@savannahstate.edu , brownuj@gmail.com
Dr. C. Vijai
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Assistant Professor Department of Commerce St.Peter’s Institute of Higher Education and Research, Avadi, Chennai-600 054 Tamil Nadu, India Email: Vijaialvar@gmail.com
Prof. Mounir BELLOUMI
Associate Editorial Board
College of Administrative Sciences, Najran University, Saudi Arabia Email: mounir.balloumi@gmail.com
Prof. P Malyadri
Editor-in-Chief
ICSSR Senior Fellow Centre for Economic and Social Studies (CESS), Begumpet, Hyderabad-500016, India Email: drpm16@gmail.com
Husam Alharahsheh
Executive Editor
Lecturer in business management, University of wales Trinity Saint David - UK Senior lecturer, Several UK and EU based higher education institutions Email: husam.helmi1@yahoo.com
Dr. Mohd Shahril Bin Ahmad Razimi
Deputy Chief-Editor
Programme Coordinator Senior Lecturer, Islamic Business School Universiti Utara Malaysia Email: shahril@uum.edu.my
Aliashraf Ahmadian
Associate Editorial Board
Marketing lecturer Graduated in the Degree of Doctor of Philosophy (phD) from University of Tehran, Iran. Email: AliAshrafAhmadian@ut.ac.ir
ZULFAN NAHRUDDIN
Executive Editor
Lecturer at Muhammadiyah University of Makassar email:- zulfan.nahruddin@unismuh.ac.id
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