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

Yazdi, Amir Karbassi; Muneeb, Farhan Muhammad; Figueiredo, Otávio; Mushtaq, Irum

doi:10.1155/2021/8846808

Cited by 13 publications

(5 citation statements)

References 115 publications

(141 reference statements)

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“…In practical terms, activities related to organizational strategy are intended to combine management processes and obtain competitive advantage, thus promoting the exchange of internal and external knowledge and strengthening the dynamics of the business ecosystem (Rua et al, 2023). It is noteworthy that the CFS related to managerial perceptions of strategy and performance indicators have an influence on aspects related to competitive advantage (Yazdi et al, 2021).…”

Section: Creation Of Competitive Advantagementioning

confidence: 99%

Impact of critical success factors and risk management on organizational results

Rampini,

Berssaneti

2024

BJO&PM

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Goal: The purpose of this study is to identify how do risk management processes and critical success factors (CSFs) impact organizational results. Design / Methodology / Approach: A qualitative research approach was applied, using a multiple case study, involving six organizations in public and private sectors of the Brazilian economy. Results: The support given by top management, the existence of a corporate governance structure, the integration of risk management across all organizational functions and the importance of stakeholder participation, both in public and private organizations, presented aspects that impact organizational outcomes, such as the preservation of reputation, increase in market value, and the creation of competitive advantage. Limitations of investigation: The present research considered only Brazilian organizations, which is a limiting factor for a possible generalization of the findings. The research can be extended to other organizations and countries, so that other contexts can be discussed and analyzed. Practical implications: Based on the findings, we designed an Organizational Results Matrix (ORM), which aims to support managers dealing with factors conditioning the company´s results. Originality / Value: The original value of the research lies in the presentation of ORM. This matrix may enrich the quality and rigor of the actions carried out in public and private sectors, providing to managers an insight into the main dimensions of CSFs and risk management process and their influence on the expected results.

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Section: Creation Of Competitive Advantagementioning

confidence: 99%

Impact of critical success factors and risk management on organizational results

Rampini,

Berssaneti

2024

BJO&PM

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“…Globally, the unprecedented COVID-19 outbreak reinforced the critical importance of rapid development vs. survival for pharmaceutical companies and had a significant impact on the medical supply chain as well [32,33]. During the COVID-19 outbreak, Govindan et al [34] created a biobjective MILP model for managing medical waste to reduce the overall costs and dangers of the population's exposure to pollution.…”

Section: Literature Reviewmentioning

confidence: 99%

A Mathematical Optimization Model for the Pharmaceutical Waste Location‐Routing Problem Using Genetic Algorithm and Particle Swarm Optimization

Aghakhani,

Pourmand,

Zarreh

2023

Mathematical Problems in Engineering

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Pharmaceutical waste management is a significant concern that poses risks to human and environmental health. The ineffective management of expired and unused medications can harm individuals and communities. This study proposes a novel approach to address the issue of pharmaceutical waste management by developing a location-routing problem (LRP) model using mixed-integer linear programing (MILP) to optimize the collection and disposal of pharmaceutical waste. The proposed model aims to minimize transportation costs, construction of collection centers, disposal costs, and carbon dioxide emissions, making it a cost-effective and environmentally sustainable approach to managing pharmaceutical waste. Initially, the feasibility, validity, and efficiency of the proposed model are examined by solving the problem in the GAMS software using CPLEX solver for small-scale problems. Sensitivity analyses are conducted to ensure the accuracy, reliability, robustness, and usefulness of the mathematical model for decision-making. In view of the inherent computational complexity of the proposed model, which is classified as nondeterministic polynomial time-hard and poses considerable difficulties when exact solutions are sought for large-scale problems, the present study resorts to two metaheuristic algorithms, specifically particle swarm optimization (PSO) and genetic algorithm (GA), as a means minimizing the computational burden. The results indicate that GA outperforms PSO in terms of objective function and solution time, with an average improvement of approximately 1% and 20%, respectively. The proposed model and algorithms provide a comprehensive approach to addressing the critical issue of pharmaceutical waste management, benefiting the healthcare industry, and society as a whole.

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“…In that sense, drug distribution companies are deserving of particular concern and detailed evaluation. More importantly, some papers (Yazdi et al, 2021) identified a set of criteria to measure the performance of the drug makers. However, the performance of PSCs depends on the logistics abilities and performance of the drug distribution companies than other supply chain actors.…”

Section: Fermatean Fuzzy Entropy and Waspas Modelmentioning

confidence: 99%

“…In that sense, drug distribution companies are deserving of particular concern and detailed evaluation. More importantly, some papers (Yazdi et al. , 2021) identified a set of criteria to measure the performance of the drug makers.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluation of the pharmaceutical distribution and warehousing companies through an integrated Fermatean fuzzy entropy-WASPAS approach

Ayteki̇n

Görçün²,

Ecer³

et al. 2022

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PurposePharmaceutical supply chains (PSCs) need a well-operating and faultless logistics system to successfully store and distribute their medicines. Hospitals, health institutes, and pharmacies must maintain extra stock to respond requirements of the patients. Nevertheless, there is an inverse correlation between the level of medicine stock and logistics service level. The high stock level held by health institutions indicates that we have not sufficiently excellent logistics systems presently. As such, selecting appropriate logistics service providers (drug distributors) is crucial and strategic for PSCs. However, this is difficult for decision-makers, as highly complex situations and conflicting criteria influence such evaluation processes. So, a robust, applicable, and strong methodological frame is required to solve these decision-making problems.Design/methodology/approachTo achieve this challenging issue, the authors develop and apply an integrated entropy-WASPAS methodology with Fermatean fuzzy sets for the first time in the literature. The evaluation process takes place in two stages, as in traditional multi-criteria problems. In the first stage, the importance levels of the criteria are determined by the FF-entropy method. Afterwards, the FF-WASPAS approach ranks the alternatives.FindingsThe feasibility of the proposed model is also supported by a case study where six companies are evaluated comprehensively regarding ten criteria. Herewith, total warehouse capacity, number of refrigerated vehicles, and personnel are the top three criteria that significantly influence the evaluation of pharmaceutical distribution and warehousing companies. Further, a comprehensive sensitivity analysis proves the robustness and effectiveness of the proposed approach.Practical implicationsThe proposed multi-attribute decision model quantitatively aids managers in selecting logistics service providers considering imprecisions in the multi-criteria decision-making process.Originality/valueA new model has been developed to present a sound mathematical model for selecting logistics service providers consisting of Fermatean fuzzy entropy and WASPAS methods. The paper's main contribution is presenting a comprehensive and more robust model for the ex ante evaluation and ranking of providers.

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

Cited by 13 publications

References 115 publications

Impact of critical success factors and risk management on organizational results

Impact of critical success factors and risk management on organizational results

A Mathematical Optimization Model for the Pharmaceutical Waste Location‐Routing Problem Using Genetic Algorithm and Particle Swarm Optimization

Evaluation of the pharmaceutical distribution and warehousing companies through an integrated Fermatean fuzzy entropy-WASPAS approach

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