Multiple Criteria Decision Making Approach Research Articles

A comprehensive risk assessment view on interval type-2 fuzzy controller for a time-dependent HazMat routing problem

Hazardous material transportation is an integral part of industries that pose significant risks. Hazardous material transportation risk of is proportional to the volume of materials transferred, the length of the link, and the population density, which varies over time. By modeling the effects of time on population density, this paper presents a multi-objective time-dependent hazardous materials routing problem for efficiently managing hazardous material transportation. The proposed model's objectives include the reduction of transportation risks and travel costs. Given the uncertainty associated with hazardous materials routing, an interval type-2 fuzzy logic controller is used to estimate risk; its inputs include population density, vehicle load, link length, and time of day. A type-2 fuzzy multi-objective evolutionary algorithm based on decomposition is used to optimize the proposed model and an adaptive large neighborhood search to enhance the local neighbor search mechanism. Additionally, by utilizing the nadir reference point, the distribution of Pareto front approximation is improved. Furthermore, a new metric is introduced to evaluate the dispersion of Pareto front approximation. The proposed method is compared to three other state-of-the-art evolutionary algorithms using eleven different performance metrics for validation. Then, using the multiple-criteria decision-making approach, the meta-heuristics algorithms are evaluated. The obtained results demonstrate the proposed solution method algorithm's competitiveness and superiority over the other three evolutionary algorithms.

An intelligent multiple-criteria decision-making approach based on sv-neutrosophic hypersoft set with possibility degree setting for investment selection

PurposeThe main purpose of this article is to characterize a novel neutrosophic hypersoft set hybrid called possibility single-valued neutrosophic hypersoft set (psv-NHSS) for evaluation of investment projects by using its aggregation operations and decision-support system.Design/methodology/approachTwo approaches are employed in this article: set-theoretic approach and algorithmic approach. The former one is used to characterize the novel notion of psv-NHSS and its aggregations. The later one is used to construct a decision-support system by using the aggregations like core matrix, maximum-valued decision, minimum-valued decision and scoring-valued decision of psv-NHSS. The adopted algorithm is implemented in real-world scenario of hydroelectric power station project evaluation for investment purpose.FindingsThe proposed model is more flexible and reliable as it addresses the limitations of literature on neutrosophic set, neutrosophic soft set and other fuzzy set-like models by considering possibility degree, hypersoft setting and neutrosophic setting collectively.Research limitations/implicationsIt has limitations for decision-making situations where selection of parameters is of uncertain nature.Practical implicationsThe scope of this study may cover a wide range of applications in many fields of mathematical sciences like artificial intelligence, optimization, multiple-criteria decision-making (MCDM), theoretical computer science, soft computing, mathematical statistics, etc.Originality/valueThe proposed model bears the characteristics of most of the relevant existing models collectively and fulfills their insufficiencies by introducing a novel approximate mapping.

A novel GIS-based MCDM approach to identify the potential eco-tourism sites in the Eastern Dooars region (Himalayan foothill) of West Bengal, India

The present study was designed to assess the capability of the novel Multiple-criteria decision-making (MCDM) method such as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) along with Analytical Hierarchy Process (AHP) in identifying the potential site of ecotourism in the Eastern Dooars region of West Bengal, India. Two popular objective weighting methods such as Entropy and Criteria Importance through Interaction Correlation (CRITIC), were used to minimize the subjectivity of AHP methods. The suitability map obtained from these applied methods showed that the northern and north-eastern parts, namely Kalchini and Kumargram blocks, were identified as the highly suitable zone for ecotourism development. Finally, the obtained suitability map was validated using receiver operating characteristic (ROC) and Area Under Curve (AUC) analysis. The AUC value of ROC was more than 0.80 for all the applied methods, indicating the reliability of all the applied models.

An Empirical Investigation to Understand the Issues of Distributed Software Testing amid COVID-19 Pandemic

Generally, software developers make errors during the distributed software development process; therefore, software testing delay is a significant concern. Some of the software mistakes are minor, but others may be costly or harmful. Since things can still go wrong—individuals encounter mistakes from time to time—there is a need to double-check any software we develop in a distributed environment. The current global pandemic, COVID-19, has exacerbated and generated new challenges for IT organizations. Many issues exist for distributed software testing that prevent the achievement of successful and timely risk reduction when several of the mechanisms on which testing is based are disrupted. The environment surrounding COVID-19 is quickly evolving on a daily basis. Moreover, the pandemic has exposed or helped to develop flaws in production systems, which obstruct software test completion. Although some of these issues were urgent and needed to be evaluated early during the distributed software development process, this paper attempts to capture the details that represent the current pandemic reality in the software testing process. We used a Fuzzy TOPSIS-based multiple-criteria decision-making approach to evaluate the distributed software testing challenges. The statistical findings show that data insecurity is the biggest challenge for successful distributed software testing.

An Integrated Fuzzy MCDM Hybrid Methodology to Analyze Agricultural Production

A hybrid model was developed by combining multiple-criteria decision-making (MCDM) with the analytic hierarchy process (AHP) and a fuzzy set to give decision support for choosing sustainable solutions to agricultural problems. Six steps were taken to build the suggested hybrid model: identifying and weighing criteria; normalizing data using fuzzy membership functions; calculating the weighting of the criteria using AHP; and selecting the best alternative for the agricultural problem. The objective of this case study is to demonstrate how agricultural production techniques (APTs) are becoming more complex as agricultural production becomes more complex. Organic agriculture aims to protect both the environment and consumer satisfaction by utilizing organic management practices that do not have the negative effects associated with conventional and genetic engineering production. Meanwhile, products obtained through conventional and genetic engineering techniques are more cost-effective. To present the superiority of the proposed fuzzy MCDM hybrid model, this problem is used as the causative agent’s dataset. Because the challenge involves a large number of competing quantitative and qualitative criteria, the assessment approach should improve the ratio of input data to output data. As a result, agricultural productivity should be controlled holistically. However, because the problem may contain both qualitative and quantitative facts and uncertainties, it is necessary to represent the uncertainty inherent in human thinking. To achieve superior outcomes, fuzzy set theory (FST), which enables the expression of uncertainty in human judgments, can be integrated with). The purpose of this study is to present a novel MCDM approach based on fuzzy numbers for analyzing decision-making scenarios. The proposed methodology, which is based on Buckley’s fuzzy analytic hierarchy process (B-FAHP) and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS), uses Buckley’s fuzzy analytic hierarchy process (B-FAHP) and fuzzy TOPSIS to determine weights and rank alternatives, respectively. As a result, we attempted to include both the uncertainty and hesitancy of experts in the decision-making process through the use of fuzzy numbers. We have three main criteria in this study: Satisfaction (C1), Economy (C2), and Environment (C3). An important objective of the current research is to build a complete framework for evaluating and grading the suitability of technologies. A real-world case study is used to demonstrate the suggested paradigm’s validity.

Underwater friction-stir welding of a stir-cast AA6061-SiC metal matrix composite: optimization of the process parameters, microstructural characterization, and mechanical properties

Abstract It is an underlying fact for the case of the joining process especially welding to have optimized parameters to achieve joints with outstanding mechanical characteristics. In the current article, using stir-cast aluminum-based alloy (Al 6061) is stir-cast with Al 6061/5%wt. silicon carbide, Al 6061/10%wt. silicon carbide, and Al 6061/18%wt. silicon carbide was welded using an underwater friction-stir welding process. Optimum welding parameters [namely, tool rotating speed (N), welding speed (S), and silicon carbide (SiC)] are investigated using analysis of variance (ANOVA) and response surface methodology (RSM) statistical approaches. High ultimate tensile strength and microhardness were set as required characteristics of quality welds. Since there are two responses and two objectives, multiple-criteria decision-making approach—response surface methodology was performed alongside ANOVA. Optimal parameters from these statistical approaches are converged to a tool rotating speed of 1,736.36 rpm, a welding speed of 11.58 mm/min, and a SiC of 16.67%, respectively. For the current inquiry, the computed ultimate tensile strength and microhardness are 984 MPa and 89.9 HV, respectively, and these values are congruent with the findings of effectiveness studies. It is deduced from this study that the optimal parameters are convergent irrespective of the two used techniques for the investigated experimental data.

A Novel Multiple-Criteria Decision-Making Approach Based on Picture Fuzzy Sets

Experts are using picture fuzzy sets (PFSs) in their probes to resolve the uncertain and vague information during the process of decision making because PFSs describe human attitudes naturally. Divergence measure (DM) plays a dominant role in discriminating between two distributions of probability and extracting consequences from that discrimination. In the present work, a novel picture fuzzy divergence measure (PF-DM) is developed between two PFSs. Some of the suggested measure’s important qualities are also discussed with particular situations to validate it. Based on the suggested PF-DM, a multiple-criteria decision-making (MCDM) model is established to grab the fuzzy information. The suggested measure’s performance is compared to that of various existing measures in the literature. An MCDM model has been proven for the usefulness of the suggested technique in dealing with real-life scenarios in the context of dengue sickness and pattern identification. Validation of the suggested MCDM model has been further investigated using validity testing. To improve the generated model, a thorough comparison with several current methodologies has been carried out while taking the time complexity (TC) factor into account.

Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review.

The influence of the ongoing COVID-19 pandemic that is being felt in all spheres of our lives and has a remarkable effect on global health care delivery occurs amongst the ongoing global health crisis of patients and the required services. From the time of the first detection of infection amongst the public, researchers investigated various applications in the fight against the COVID-19 outbreak and outlined the crucial roles of different research areas in this unprecedented battle. In the context of existing studies in the literature surrounding COVID-19, related to medical treatment decisions, the dimensions of context addressed in previous multidisciplinary studies reveal the lack of appropriate decision mechanisms during the COVID-19 outbreak. Multiple criteria decision making (MCDM) has been applied widely in our daily lives in various ways with numerous successful stories to help analyse complex decisions and provide an accurate decision process. The rise of MCDM in combating COVID-19 from a theoretical perspective view needs further investigation to meet the important characteristic points that match integrating MCDM and COVID-19. To this end, a comprehensive review and an analysis of these multidisciplinary fields, carried out by different MCDM theories concerning COVID19 in complex case studies, are provided. Research directions on exploring the potentials of MCDM and enhancing its capabilities and power through two directions (i.e. development and evaluation) in COVID-19 are thoroughly discussed. In addition, Bibliometrics has been analysed, visualization and interpretation based on the evaluation and development category using R-tool involves; annual scientific production, country scientific production, Wordcloud, factor analysis in bibliographic, and country collaboration map. Furthermore, 8 characteristic points that go through the analysis based on new tables of information are highlighted and discussed to cover several important facts and percentages associated with standardising the evaluation criteria, MCDM theory in ranking alternatives and weighting criteria, operators used with the MCDM methods, normalisation types for the data used, MCDM theory contexts, selected experts ways, validation scheme for effective MCDM theory and the challenges of MCDM theory used in COVID-19 studies. Accordingly, a recommended MCDM theory solution is presented through three distinct phases as a future direction in COVID19 studies. Key phases of this methodology include the Fuzzy Delphi method for unifying criteria and establishing importance level, Fuzzy weighted Zero Inconsistency for weighting to mitigate the shortcomings of the previous weighting techniques and the MCDM approach by the name Fuzzy Decision by Opinion Score method for prioritising alternatives and providing a unique ranking solution. This study will provide MCDM researchers and the wider community an overview of the current status of MCDM evaluation and development methods and motivate researchers in harnessing MCDM potentials in tackling an accurate decision for different fields against COVID-19.

Optimization of ZVAl based oxidation and reduction process conditions: Selection of the most suitable process by multiple-criteria decision-making approach

The use of zero valent aluminum (ZVAl) has attracted attention as an effective agent in the oxidation and reduction of pollutants due to its electron donor nature. In this study, the removal of the target pollutant Sunfix red S3B (SR-S3B) azo dye with ZVAl based processes was investigated. For maximum dye removal efficiency, the operating conditions of the processes are optimized with Box Behnken Design. With the optimum conditions of the (PS+ZVAl) oxidation process (PS dose of 12.5 g anion/L, duration of 134 min, pH of 2, ZVAl dose of 3.5 g/L) 94.95% dye removal, and with the optimum conditions of the (H2O2+ZVAl) oxidation process (H2O2 dose of 0.20 M, duration of 180 min, pH of 2, ZVAl dose of 1.44 g/L) 55% dye removal efficiency was obtained. In the (O2 status+ZVAl) reduction process, 77.27% dye removal efficiency was obtained under optimum conditions (anaerobic conditions, duration of 14.8 min, pH of 2, ZVAl dose of 1.43 g/L). With the Pareto analysis of (PS+ZVAl), (O2 status+ZVAl) and (H2O2+ZVAl) processes, the parameters with the highest effect were determined as (ZVAl dose)2 (37.42%), O2 status (29.56%), and (H2O2xpH) (28.38%) respectively. The optimized processes were evaluated by the PROMETHEE method, taking into account the criteria of dye removal efficiency, operating cost and possible residues of oxidizing/reducing agents. The preference ranking of the processes was determined as (O2 status+ZVAl)> (PS+ZVAl)> (H2O2+ZVAl).

Evaluating the operation performance of the Serbian transport Freight system by using multiple criteria decision-making technique

Freight transport is a composite dynamic system that forms the unity of the infrastructure, vehicles, and personnel and which has its purpose or aim. Evaluating operation performance for freight transport systems is important for the government, companies, and users. This paper will use one of the most famous Multiple Criteria Decision-Making (MCDM) techniques to assess the operational performance of freight transport systems. At beginning, the authors will create the evaluation indicator system based on official data with four basic indicators and two sub-indicators for freight transport. These operational data/indicators represent the input of the chosen MCDM method. After that, the Analytic Hierarchy Process (AHP) method will use to calculate the indicator and sub-indicators weight and also will use to calculate the universal evaluate values and rankings of each transport mode performance. The Serbian freight transport system for the 2021st year will be selected as a case study for testing the AHP method within the MCDM approach; the associated suggestions to freight transport will also be given.

Selection of an alternative based on interval-valued hesitant picture fuzzy sets

Motivated by interval-valued hesitant fuzzy sets (IVHFSs) and picture fuzzy sets (PcFSs), a notion of interval-valued hesitant picture fuzzy sets (IVHPcFSs) is presented in this article. The concept of IVHPcFSs is put forward and some operational rules are developed to deal with it. The cosine similarity measures (SMs) are modified for IVHPcFSs to deal with interval-valued hesitant picture fuzzy (IVHPcF) data and the linear programming (LP) methodology is used to find out the criteria’s weights. A multiple criteria decision making (MCDM) approach is then developed to tackle the vague and ambiguous information involved in MCDM problems under the framework of IVHPcFSs. For the validation and strengthen of the proposed MCDM approach a practical example is put forward to select the educational expert at the end.

Social network multiple-criteria decision-making approach for evaluating unmanned ground delivery vehicles under the Pythagorean fuzzy environment

With the rapid development of instant delivery, the shrinking labor population and prevailing contact-free economy, companies have launched unmanned ground delivery vehicles (UGDVs) to replace human distribution with machines. To meet the requirements for selecting UGDVs and achieve better applications in community delivery, a multi-criteria decision-making (MCDM) framework, combining the self-confidence aggregation approach and social trust network, is proposed in this study. Based on the internal characteristics of UGDVs, a multi-criteria comprehensive evaluation system for UGDVs is constructed. Then, a trust propagation and aggregation mechanism to yield expert weights based on a social trust network is suggested. Further, a self-confidence Pythagorean fuzzy aggregation operator is proposed to enhance the credibility of the decision results and compensate for the defects of existing methods. Finally, a practical case is considered to demonstrate the complete process of the MCDM model and to conduct a comparative analysis and sensitivity analysis of the model.

Diversification of gas sources to improve security of supply using an integrated Multiple Criteria Decision Making approach

A robust and resilient gas network is crucial for ensuring supply security and economic growth, which can be achieved by having a diverse, cost-efficient, and sustainable gas supply. This study highlights the importance of natural gas and natural gas networks in a low-carbon future and examines the drivers of gas supply diversification. A comprehensive review of various potential gas sources based on cost, availability, quality, and sustainability is performed. An integrated Multiple Criteria Decision Making (MCDM) approach is developed to identify the best alternative gas source for diversifying the gas supply. The implementation of the integrated MCDM approach is demonstrated using 2 case studies: Ireland and Portugal, both countries having significant dependencies on gas imports to supply their gas demand. Developing biomethane production is identified as the most suitable option for diversification in Ireland, followed by floating LNG. Expanding permanent gas storage capacity is identified as the most suitable diversification option for Portugal, followed by the completion of the on-going pipeline interconnector project.

A Review on Weight Process Method and its Classification

Weight Process Method (WPM) is a popular number Criterion Results Analysis (MCDA) / Multiple Criteria Decision Making (MCDM) method. This is the sum of the weights Similar to the model (WSM). The main difference is, In the main mathematical function there is now multiplication instead of addition. MCDM is multifaceted, inconsistent, standard and / or quantitative Consensus on integrating alternative performance into criteria Is a technique for creating a solution that requires feedback. To calculate the weighted product, we will multiply the value of each attribute in every column row-wise. The value with the highest weighted product is given the higher rank. Like all MCDA / MCDM methods, many Described in terms of decision making criteria The result is a finite set of alternatives. For each end The substitute is also multiplied by several ratios and compared with the others, One for each end criterion. Weighted shading mode () like density mode Colors that represent density in each pixel Draw markers using, but optional With weighting integration. To provide the final weighing result How the coordinates weigh in each pixel You can configure which are connected. Multiple criteria for decision making (MCDM) size and Complex decision making (DM) involving quality factors Is considered a tool. In recent years, many MCDM Techniques and approaches optimal feasibility Recommended to select options. In statistics, a weighted median of a sample is the 50% weighted percentile. … Like the median, it is useful as an estimator of central tendency, robust against outliers

Blockchain drivers to achieve sustainable food security in the Indian context

Blockchain has the potential to improve sustainable food security due to its unique features like traceability, decentralized and immutable database, and smart contract mechanisms. However, blockchain technology is still in the early stages of adoption in particular in agricultural applications. In this context, this article aims to identify blockchain drivers to achieve sustainable food security in the Indian context and model them using an integrated MCDM (Multiple Criteria Decision Making) approach. The blockchain adoption drivers are identified through an exhaustive literature review and opinions from domain experts from industry, academia, and Agriculture Supply Chain (ASC) stakeholders. Subsequently, the integrated MCDM approach is developed by combining Total Interpretive Structural Modelling (TISM) and Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), which does not only investigate the interrelation between the identified constructs and builds hierarchy but also determines the intensity of the causal interrelationships. At a later stage, Fuzzy Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) is used to cluster the identified drivers to evaluate the importance of each driver. The results reveal that Traceability, Real-time information availability to agro-stakeholder, and Decentralized and immutable database are the most significant drivers. Policymakers, governmental organizations and other relevant stakeholders may utilize the information about the interrelationship between these drivers and their influential power, to frame suitable strategies for enhancing the adoption rate of blockchain in the Indian ASC.

A hybrid multiple‐criteria decision‐making approach for selecting optimal automotive brake friction composite

In this research article, a hybrid multiple-criteria decision-making approach was implemented to select the optimal brake friction formulation according to several conflicting performance-defining criteria. Friction material formulations based on different abrasives (magnesium oxide, iron oxide, zinc oxide, aluminum oxide, titanium dioxide, zirconium dioxide, and silicon dioxide) were designed, fabricated, and tested for various tribological properties. The inclusions of aluminum oxide proved best from performance and fade coefficient of friction, friction stability, friction fluctuations, and friction variability point of view but confirmed worst in terms of wear and disc temperature rise. The lowest wear and lowest rise in disc temperature were exhibited by zinc oxide added composite. The highest recovery coefficient of friction was displayed by silicon dioxide added composite. Since no single composite alternative could merely satisfy all the desired attributes. To find the optimum composite option for automotive braking application, hybrid analytic hierarchy process (AHP)–criteria importance through intercriteria correlation (CRITIC)–technique for order of preference by similarity to ideal solution (TOPSIS) was used to make the final decision. The results show that the formulation with titanium dioxide as abrasive exhibits the optimal properties.

A novel hesitant-fuzzy-based group decision approach for outsourcing risk

Outsourcing is recognized as a strategic instrument for companies to move towards diversified operation advantages and efficient global market. However, outsourcing agreements may fail due to insufficient risk consideration and evaluation. This requires an effective risk evaluation approach that necessitates an entire comprehension of the system, its requirements and dimensions. This paper proposes a novel fuzzy group multiple-criteria decision-making approach through integrating triangular fuzzy hesitant sets (TFHS), Failure Mode and Effect Analysis (FMEA) and combined compromise solution (CoCoSo) algorithm. This approach (F-FMEA-CoCoSo, henceforth) analyzes and evaluates the possible risks level of alternative outsourcing providers. It hereby provides measurable information for managers according to the linguistic opinions of industrial experts. Utilization of hesitant fuzzy variables allows decision making participants to state their opinion more precisely. A case study of an Iranian chemical company is used to exemplify the applicability and suitability of the proposed F-FMEA-CoCoSo approach. The model reflects an analytical approach while experts are experiencing considerable uncertainty in risky conditions of outsourcing operations. CoCoSo contains an integrated approach of compromise solutions and its utilization enables investigators to assure results reliability which is proven via the sensitivity analysis. Through this study, we found that risk evaluation of outsourcing providers must consider four key-factors: multi-experts, multi-criteria, multi-uncertainties and measurability.

Dealing with Water Conflicts: A Comprehensive Review of MCDM Approaches to Manage Freshwater Ecosystem Services

This paper presents a comprehensive review of the application of Multiple-Criteria Decision-Making (MCDM) approaches exclusively to water-related freshwater ecosystem services. MCDM analysis has been useful in solving conflicts and it works well in this framework, given the serious conflicts historically associated with water use and the protection of freshwater ecosystems around the world. In this study, we present a review of 150 papers that proposed the use of MCDM-based methods for the social, economic, or ecological planning and management of water ecosystem services over the period 2000–2020. The analysis accounts for six elements: ecosystem service type, method, participation, biogeographical realm, waterbody type, and problem to solve. A Chi-square test was used to identify dependence between these elements. Studies involving the participation of stakeholder groups adopted an integrated approach to analysing sustainable water management, considering provisioning, regulating, and cultural services. However, such studies have been in decline since 2015, in favour of non-participatory studies that were strictly focused on ecological and provisioning issues. Although this reflects greater concern for the health of freshwater ecosystems, it is a long way removed from the essence of ecosystem services, which entails an integrated approach to the interrelationships between hydrology, landscapes, ecology, and humans.

Robust measurement of innovation performances in Europe with a hierarchy of interacting composite indicators

ABSTRACT For a long time, the measurement of innovation has been at the forefront of policymakers' and researchers' agenda worldwide. Therefore, there is an ongoing debate about which indicators should be used to measure innovation. Recent approaches have favoured the use of composite innovation indicators. The European Innovation Scoreboard (EIS) is a relevant tool for benchmarking innovation in Europe. Still, the EIS lacks a proper scheme for weighting the included indicators according to their relative importance. Moreover, despite there is a consensus on the importance of interaction between different dimensions of innovation, there is no composite indicator taking into account of this. We propose an appraisal methodology permitting to take into consideration the interaction of dimensions to be aggregated and robustness concerns related to the elicitation of the weights assigned to the elementary indicators structured in a hierarchical way. With this aim, we apply a multiple-criteria decision-making approach being the conjunction of three methodologies, namely, the multiple-criteria hierarchy process, the Choquet integral and the stochastic multicriteria acceptability analysis. It helps the users to rank and benchmark countries' innovation performance at partial and global level taking into account the importance and interaction of dimensions as well as robustness concerns.

Critical Success Factors for Competitive Advantage in Iranian Pharmaceutical Companies: A Comprehensive MCDM Approach

The unprecedented COVID-19 outbreak strengthened the critical manifestation of the rapid development vs. survival for pharmaceutical companies, deploying strategic conduct worldwide. This study therefore explores the endogenous relationship among pharmaceutical companies’ manufacturing strategy and their performance indicators within the ambit of creating a long-lasting competitive advantage in turbulent times. Very often, it is not possible to launch a cause-effect relationship between performance and their drivers. To achieve this end, multiple-criteria decision-making (MCDM) techniques are employed in a hybrid fashion in this study. The notion has simultaneously ranked critical success factors (CSFs) in the manufacturing strategy and performance indicators in the limelight of managerial perceptions, while controlling the inherent bias concerning the causality direction in the ambit of these two entrenched concepts. A case study on the Iranian pharmaceutical companies is piloted to demonstrate this hybrid-fashion multifarious approach. Overall, the results revealed the most pertinent CSFs that reached superior-performance echelons in the Islamic Republic of Iran.