Ordinal Priority Approach (OPA) in Multiple Attribute Decision-Making

Ataei, Younes; Mahmoudi, Amin; Feylizadeh, Mohammad Reza; Li, Dengfeng

doi:10.1016/j.asoc.2019.105893

Cited by 180 publications

(117 citation statements)

References 30 publications

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“…The steps of OPA has been presented as follows (Ataei et al, 2020): Step 1: Determining the criteria: The decision maker should identify essential criteria and sub‐criteria. Step 2: Identifying and ranking the experts (in the case of group decision making): if there are more than one expert, then the problem is group decision making. In this step, the experts should be specified, and the priority of them should be determined.…”

Section: Ordinal Priority Approachmentioning

confidence: 99%

“…Contrary to methods such as TOPSIS, ELECTRE, and VIKOR, which require the determination of positive and negative ideal solutions, OPA does not require such solutions whatsoever. OPA was proposed by Ataei, Mahmoudi, Feylizadeh, and Li (2020) that can dominate all the issues mentioned above. Therefore, the current study attempts to extend the OPA under uncertainty conditions for the first time.…”

Section: Introductionmentioning

confidence: 99%

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Sustainable Supplier Selection in Megaprojects: Grey Ordinal Priority Approach

et al. 2020

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Due to mounting environmental and social challenges, supplier selection has become one of the most critical tasks of project‐oriented organizations. Because supplier selection can affect the long‐term success and profitability of the organizations and their projects, directly, embracing sustainability can add value in the equation. Considering sustainability measures can positively guide project managers in making better decisions for the projects in the long term. Therefore, the current study attempts to provide a conceptual model for selecting the best supplier based on a sustainability framework in megaprojects. Meanwhile, decision‐making methods can be employed as a proper tool to find the best supplier. Ordinal priority approach (OPA) is a recent development in multiple criteria decision making (MCDM), while it has many benefits compared with other methods like analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). However, this method cannot consider multiple ranks during the decision‐making process, and using an uncertainty approach feels strongly. Grey systems theory (GST) can consider uncertainties with no need for large sample or proposing membership function. Hence, the current study employed the GST to consider multiple ranks for criteria and alternatives in the OPA method. This is the first time that a sustainable supplier selection framework has been presented for megaprojects with the aid of the Grey OPA (OPA‐G) method. Finally, a case study has been examined to evaluate the performance of the proposed approach. The results show that the proposed approach can be used in real‐world situations and it has acceptable performance under uncertainty conditions.

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Section: Ordinal Priority Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sustainable Supplier Selection in Megaprojects: Grey Ordinal Priority Approach

et al. 2020

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“…Lastly, the OPA-F is presented along with the definitions of associated variables. Here, it should be noted that the authors are well aware of the pedagogic debate in the multiple criteria decision-making literature, where some scholars distinguish criteria from attributes while emphasizing criteria to be a more general term for attributes (Ataei et al 2020 ; Ekel et al . 2019 ; Ploskas and Papathanasiou 2019 ) although others do not (see, e.g., Javed et al 2020b ; Mahmoudi et al 2019b ; Rezaei 2016 ), sometimes deliberately (Guo and Zhao 2017 ).…”

Section: Preliminaries Of Opa-fmentioning

confidence: 99%

“…Different methods of aggregation of data (e.g., average versus geometric mean) can also influence results and ranks (Lin et al 2020 ; Saaty and Vargas 2007 ). To solve these issues a team of researchers has recently proposed a breakthrough methodology in multiple attribute decision-making (see, Ataei et al 2020 ). Their method produced reliable results when compared with that of different MADM methods like the AHP, the BWM, TOPSIS, VIKOR, PROMETHEE, and QUALIFLEX.…”

Section: Introductionmentioning

confidence: 99%

“…Their methodology is called the Ordinal Priority Approach (OPA) and is a linear programming based intelligent model that is free from several limitations associated with the theory of MADM for decades. For instance, the OPA does not make use of pairwise comparison matrix, decision-making matrix (no need for numerical input), normalization methods, averaging methods for aggregating the opinions of experts (in group decision making), among others (Ataei et al 2020 ).…”

Section: Introductionmentioning

confidence: 99%

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Gresilient supplier selection through Fuzzy Ordinal Priority Approach: decision-making in post-COVID era

2021

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Because of the COVID-19 outbreak, the supply of both essential and non-essential goods and services has been unprecedentedly disrupted. In the absence of any playbook, the need for innovative technologies to aid recovery from the Supply Chain (SC) disruptions quickly and effectively becomes persistent. The study aims to develop an innovative decision-making technology to handle the supplier selection problems arising from the frequent impreciseness and incompleteness in the nowadays' SC reports within the framework of the gresilient supply chain management. Through the integration of green and resilience aspects of the SCs, the supply chain 'gresilience' has been conceptualized. In light of this construct and based on the data collected from a manufacturing firm, the study deploys a two-fold decomposition of the core algorithm of the Ordinal Priority Approach (OPA), one for attributes and other for alternatives. It extends the OPA to the Fuzzy OPA (OPA-F) for solving the supplier selection problems. The study illustrates how green and resilience aspects of the SC can be integrated to better understand the gresilient suppliers in the wake of the SC disruptions. A novel construct of SC Gresilience is also furnished along with a novel definition of SC Gresilience. It also provides an innovative SC decision-making technology to help procurement managers to evaluate their suppliers. The resultant framework can help them better prepare for the COVID-19 like disruptions in the future.

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Hard dimensions evaluation in sustainable supply chain management for environmentally adaptive and mitigated adverse eco‐effect environmental policies

et al. 2023

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In the oil and gas industry, adopting policies that can reduce the negative environmental effect is vital. Environmentally Sustainable Supply Chain Management (ESSCM) is an approach to carrying out Supply Chain Management (SCM) in an eco‐friendly manner and according to environmental requirements. There are different environmental policies that companies can apply based on their resource availability. Therefore, this study aims to evaluate the impact of hard dimensions on Environmentally Adaptive (EA) and Mitigated Adverse Eco‐Effect (MAE) policies in the oil and gas industry. To rank the data, Bayesian Best‐Worst Method (BWM) and Ordinal Priority Approach (OPA) have been applied. Cause‐and‐effect relationships are then calculated by employing the Decision‐Making Trial and Evaluation Laboratory (DEMATEL) technique. The results indicate that the ranking of the hard dimensions varies based on the companies' business policies and their new product/technology development projects. In other words, the findings of this research demonstrate that ‘innovation’ is the crucial dimension in companies that are focussed on developing eco‐friendly products while ‘technologies for cleaner production’ is the most important dimension in the companies attempting to reduce destructive consequences on the environment. In both types of the company policies, ‘lean manufacturing’, ‘total quality management’, and ‘institutional pressures’ are the key dimensions for a successful implementation of ESSCM while the least important dimensions include ‘supplier relationship management’, ‘green purchasing’, and ‘green logistics’. The findings of this research can assist the decision‐makers in the oil and gas sector in prioritising and identifying the interrelationship of the dimensions that significantly impact the ESSCM.

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Ordinal Priority Approach (OPA) in Multiple Attribute Decision-Making

Cited by 180 publications

References 30 publications

Sustainable Supplier Selection in Megaprojects: Grey Ordinal Priority Approach

Sustainable Supplier Selection in Megaprojects: Grey Ordinal Priority Approach

Gresilient supplier selection through Fuzzy Ordinal Priority Approach: decision-making in post-COVID era

Hard dimensions evaluation in sustainable supply chain management for environmentally adaptive and mitigated adverse eco‐effect environmental policies

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