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A Novel Fusion Method for Enhanced Multi-Criteria Decision-Making in Energy Management: Integrating Analytic Hierarchy Process

This paper suggests a novel fusion approach of combining Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to enhance multi-criteria decision-making for energy management. In this way, by integrating the two powerful methodologies, the fusion approach is enabled that allows for dealing with the complex and highly dynamic character of energy management decisions for which there is required the careful consideration of many conflicting criteria. The method uses A to derive weightings for each decision criterion via AHP based on expert judgments, ensuring all relevant factors are systematically considered proportionately. Subsequently, TOPSIS is applied to evaluate and rank the alternatives such that the most effective energy solutions close to the ideal solution are identified. This integration of AHP with TOPSIS leads to comprehensive analysis that draws both the strengths of these techniques and provides a powerful tool to make informed and balanced decisions in the energy sector. The effectiveness of this fusion method, when applied, could then lead to the attainment of subtler findings and dependable suggestions, making it a beneficial contribution to this field of energy management.

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Murodjon Sultanov mail -
Iroda Abdullayeva mail -
Botirjon Karimov mail
link https://doi.org/10.54216/FPA.150225

Volume & Issue

Vol. Volume 15 / Iss. Issue 2

Details open_in_new

Exploring Challenges and Strategies in Managing Remote and Distributed Teams amidst the Rise of Digital Nomadism

This research investigates the evolving landscape of remote work and distributed teams in the context of the growing phenomenon of digital nomadism. As remote work becomes increasingly prevalent, organizations face unique challenges in managing geographically dispersed teams while accommodating the preferences and lifestyles of digital nomads. This study combines qualitative interviews with HR professionals and digital nomads, along with a quantitative survey of remote workers, to identify key challenges and strategies in managing remote and distributed teams amidst the rise of digital nomadism.

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Nilufar Ismaılova mail
link https://doi.org/10.54216/JSDGT.040106

Volume & Issue

Vol. Volume 4 / Iss. Issue 1

Details open_in_new

Impact of FDI on Sustainable Growth in Belt and Road Economies

This paper investigates the relationship between foreign direct investment and economic growth in Belt and Road countries during 1990–2020. Our findings suggest that a 10% increase in FDI relative to GDP is associated with only a 0.9 percentage-point increase in GDP growth. The results hold after including control variables. The results can be explained by the factors that encourage investors and companies to invest their money in foreign projects, including relatively lower deployment costs, access to resources, a favorable financial environment, and developed financial markets. These elements collectively shape the impact of FDI on economic growth in Belt and Road countries. Future research on the FDI–growth nexus in Belt and Road countries should concentrate on causal links and potential indirect pathways by which FDI can influence economic growth.

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Zebo KULDASHEVA mail
link https://doi.org/10.54216/JSDGT.040207

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new

Business Intelligence for Bottleneck-Sensitive International Market Entry Screening

An international expansion team must decide which candidate markets warrant costly commercial due diligence. Regulation-only rankings can overlook the services and operating processes needed to conduct business. We develop a reproducible business intelligence screen using the three published pillars of the World Bank’s Business Ready 2025 for 101 economies. The analysis compares a regulation-led shortlist with a noncompensatory weakest-pillar rule, tests its sensitivity to shortlist capacity and alternative aggregation, and examines a mechanical one-pillar improvement scenario. Public Services is the lowest pillar in 67 economies and Operational Efficiency in 31. Regulation exceeds services by 12.36 points on average (95% bootstrap interval 10.52–14.12). The regulation-led and bottleneck-led top 20 share 11 economies, so nine due-diligence candidates change; their equal-weight and bottleneck-led counterparts share 18. Raising the lowest pillar hypothetically by ten points increases the resulting minimum by 6.63 points on average because another pillar may become binding. The output identifies markets requiring checks of service delivery or operational execution before a site-selection decision. Its rankings are transparent decision rules applied to official scores, not World Bank rankings, investment-return estimates, or evidence of causal reform effects.

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Asifa Iqbal mail -
Shahid Mahmood mail
link https://doi.org/10.54216/AJBOR.150103

Volume & Issue

Vol. Volume 15 / Iss. Issue 1

Details open_in_new

Temporal Validation of Case-Mix-Aware Credit-Card Complaint Response Analytics

Complaint dashboards often pool unlike cases and report an overall resolution rate. For a financial-services operations team, that average can conceal which issues account for redress workload and whether a triage signal remains useful on later cases. We analyze 75,988 publicly reported U.S. credit-card complaints received in 2024. The outcome is the company’s recorded “closed with monetary relief” category, not a verified payment amount or customer satisfaction. Intake issue, sub-issue, submission channel, and company identify a transparent logistic screening model trained on January–September records and evaluated on October–December records. Report-related issues comprise 31.9%of complaints but have a 0.63% monetary-relief rate, compared with 19.16% for other issues. An exact shift-share decomposition attributes 1.81 of the 2.64 percentage points of decline from the first to fourth quarter to changing issue mix. Issue alone achieves an out-of-time area under the receiver operating characteristic curve (AUC) of 0.819; adding sub-issue and channel raises it to 0.831. A cross-company specification reaches 0.873 (95% bootstrap interval 0.867–0.878) and captures 39.4% of recorded monetary-relief responses in its highest-scoring tenth of holdout cases. The company term captures institutional and routing differences, so that result does not measure issuer quality or the gain attainable within a single firm. Case-mix-aware reporting and temporal validation support staffing review queues without automating redress decisions.

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Irina V. Pustokhina mail -
Denis A. Pustokhin mail
link https://doi.org/10.54216/AJBOR.150104

Volume & Issue

Vol. Volume 15 / Iss. Issue 1

Details open_in_new

From Demand Signals to Retail Decisions in Business Intelligence Research

Retail analytics has moved beyond improving point forecasts, yet evidence about the value of a forecast for pricing, replenishment, fulfillment, and managerial adoption remains dispersed. This structured review compares 36 journal studies published from 2023 through 2025, identified within a search window ending in January 2026, across four connected areas: demand forecasting (12), pricing and commercial levers (7), inventory and fulfillment (8), and decision systems (9). Each study is examined for its information setting, analytic approach, decision connection, and evidence boundary. The synthesis identifies four recurring discontinuities: sales data can conceal unmet demand; forecast scores can misrank policies; a policy that works in a model may be infeasible in a distributed retail organization; and staff may override recommendations whose value has not been made legible. A decision-centered evaluation structure links data availability, uncertainty estimation, feasible action, adoption, and realized economic outcomes. The paper develops a research agenda around observable-demand corrections, decision-calibrated uncertainty, joint pricing and fulfillment, transportable evaluations, and human-in-the-loop deployment. The review is deliberately bounded rather than a claim of exhaustive coverage or pooled effect sizes. It offers business intelligence researchers a common basis for studying whether analytical improvements survive the operational decisions they are meant to inform.

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Mustafa Musa mail -
Raden Nur Rachman Dzakiyullah mail
link https://doi.org/10.54216/AJBOR.150105

Volume & Issue

Vol. Volume 15 / Iss. Issue 1

Details open_in_new

On Refined Netrusophic Fractional Calculus

Depending on the geometric isometry (AH-Isometry), it has been proven that every Neutrosophic real function is equivalent to three real functions. Then, the foundation of the Refined Netrusophic calculus was established, where new definitions of Refined Netrusophic integration and Refined Netrusophic differentiation were introduced, along with some illustrative examples. Following that, definitions for the Refined Netrusophic gamma function and Refined Netrusophic beta function were presented to pave the way towards achieving the desired goal, which is Refined Netrusophic Fractional calculus.

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Mohamed Nedal Khatib mail -
Ahmed Hatip mail
link https://doi.org/10.54216/IJNS.240201

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new

Reliability Function Estimated for Generalized Exponential Rayleigh Distribution Under Type-I Censored Data and Fuzzy Data

In this paper, maximum likelihood estimation method (MLEM), one of the most well-liked and frequently applied classic methods, is used to estimate the two scale and one shape parameters of the Generalized Exponential-Rayleigh distribution for type-I censored data, which is one of the most Rights censored data. Based on an iterative process to get approximated values for these two scale parameters and one shape parameter using the Newton-Raphson method to locate estimate value for these parameters by using the simulation procedure utilizing monte-Carlo technique to find Reliability function underneath various sample sizes and the initial values are different for the parameters for all estimated parameters of Generalized Exponential-Rayleigh by implement the initial value in the MATLAP program, Subsequently, conducting a comparative analysis between the estimated reliability function and its non-estimated counterpart employing the mean squares error methodology. In the last finding the pdf function f (t), reliability function R (t) and hazard function h (t) for simulation data. Also, we provide some examples to clarify how can we apply our results on fuzzy data tables

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Zainab A. Aldraji mail -
Rehab Noori shalan mail
link https://doi.org/10.54216/IJNS.240202

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new

RETRACTED ARTICLE: Plithogenic Sociogram based Plithogenic Cognitive Maps Approach in Sustainable Industries

The theory of Plithogeny is primarily attribute based. Plithogenic Sociogram (PS) and Plithogenic cognitive maps (PCM) are distinct decision-making approaches developed to deal with attributes. This paper proposes an integrated decision-making model combining the approaches of PS with PCM and this sets the beginning of new genre of PCM. The development of this model is applied in investigating the association between the factors pertinent to the promotion of sustainable industries.  This work also compares the working of the proposed integrated model of PCM with PS and the independent working of PCM model. The results are more promising to the proposed integrated approach and this paper strongly emphasises the efficacy of this hybrid approach. The blended model of PCM with PS is efficient in handling complex decision circumstances and this approach shall be extended to other kinds of Plithogenic representations.

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N. Angel mail -
Sulbha Raorane mail -
N. Ramila Gandhi mail -
R. Priya mail -
P. Pandiammal mail -
Nivetha Martin mail
link https://doi.org/10.54216/IJNS.240203

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new

Enhancing Project Selection with Neutrosophic TOPSIS: Navigating Uncertainty in Post-Pandemic Decision-Making

This article explores the implementation of Neutrosophic TOPSIS, an advanced decision-making framework that extends classical and fuzzy set theories to handle the complexities of project selection amid uncertainty and indeterminacy. Neutrosophic sets are characterized by three parameters: truth, indeterminacy, and falsehood, which allow for a nuanced assessment of alternatives against defined criteria. Utilizing neutrosophic scales and expert evaluations, this method prioritizes projects by efficiently balancing multiple truth levels and addressing specific challenges such as judicial process optimization and labor education enhancement. The case study within the article demonstrates the application of Neutrosophic TOPSIS to select the most suitable project for improving labor relations and judicial efficiency in a post-pandemic world. The methodology proved effective in identifying the Digital Platform for Labor Education project as the optimal solution, given its alignment with strategic objectives and potential to handle identified challenges robustly. Future work could integrate Neutrosophic TOPSIS with other decision-making models and expand its application to more complex scenarios, potentially incorporating automated tools for a broader and more dynamic evaluation process.

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Frantz Dimitri V. Barragan mail -
Felipe Garcés Cordova mail -
María J. Calderon Velásquez mail -
Layal Kallach mail
link https://doi.org/10.54216/IJNS.240204

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new