An integrated grey-based multi-criteria decision-making approach for supplier evaluation and selection in the oil and gas industry

Purpose The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect industrial players, including that of the host countries. Supplier selection is one of the most important decisions taken by managers of this industry that affect their supply chain operations. However, determining suitable suppliers to work with has become a phenomenon faced by these managers and their organizations. Furthermore, identifying relevant, critical and important criteria needed to guide these managers and their organizations for supplier selection decisions has become even more complicated due to various criteria that need to be taken into consideration. With limited works in the current literature of supplier selection in the oil and gas industry having major methodological drawbacks, the purpose of this paper is to develop an integrated approach for supplier selection in the oil and gas industry. Design/methodology/approach To address this problem, this paper proposes a new uncertain decision framework. A grey-Delphi approach is first applied to aid in the evaluation and refinement of these various available criteria to obtain the most important and relevant criteria for the oil and gas industry. The grey systems theoretic concept is adopted to address the subjectivity and uncertainty in human judgments. The grey-Shannon entropy approach is used to determine the criteria weights, and finally, the grey-EDAS (evaluation based on distance from average solution) method is utilized for determining the ranking of the suppliers. Findings To exemplify the applicability and robustness of the proposed approach, this study uses the oil and gas industry of Iran as a case in point. From the literature review, 21 criteria were established and using the grey-Delphi approach, 16 were finally considered. The four top-ranked criteria, using grey-Shannon entropy, include warranty level and experience time, relationship closeness, supplier’s technical level and risks which are considered as the most critical and influential criteria for supplier evaluation in the Iranian oil and gas industry. The ranking of the suppliers is obtained, and the best and worst suppliers are also identified. Sensitivity analysis indicates that the results using the proposed methodology are robust. Research limitations/implications The proposed approach would assist supply chain practicing managers, including purchasing managers, procurement managers and supply chain managers in the oil and gas and other industries, to effectively select suitable suppliers for cooperation. It can also be used for other multi-criteria decision-making (MCDM) applications. Future works on applying other MCDM methods and comparing them with the results of this study can be addressed. Finally, broader and more empirical works are required in the oil and gas industry. Originality/value This study is among the first few studies of supplier selection in the oil and gas industry from an emerging economy perspective and sets the stage for future research. The proposed integrated grey-based MCDM approach provides robust results in supplier evaluation and can be used for future domain applications

Integration of an Improved Grey-Based Method and Fuzzy Multi-Objective Model for Supplier Selection and Order Allocation

For multi-attribute decision making (MADM) problems, a grey based approach (LI) had been developed to evaluate, rank and select the best suppliers. The method calculates a grey possibility degree between compared suppliers alternatives set and positive ideal referential alternative. The drawback of the method is that the negative ideal referential alternative is not considered in evaluating and ranking of the alternatives. Moreover, the method can only consider interval fuzzy number as input data and real number is neglected. Based on this model and other MADM methods, all demand was sold by the best supplier. In other cases, if the best supplier cannot satisfy all demand, multi-objective programming is used to formulate the problem and assign optimum order quantities to the best suppliers (multi-sourcing). Some techniques, such as goal programming (GP) approach, ε-Constraint method, Reservation level (RL) driven Tchebycheff procedure (RLTP) method had been proposed to solve the multi-objective models. It may be a problem that these techniques traced back to more than 10 years ago. Therefore, there may be still the need to produce a new technique in order to solve the multi-objective models. In this study, to overcome the first drawback, the LI method was improved based on the concepts of technique for order preference by similarity to ideal solution (TOPSIS) to consider both the positive and the negative ideal referential alternative for evaluation of the suppliers. The improved version of the LI method is called the I.LI method. Based on the concepts of TOPSIS, the chosen alternative should have the shortest distance from the positive ideal solution and the farthest from the negative ideal solution. Moreover, in order to solve the problems, a new grey based method (NG) based on the TOPSIS concepts was proposed that can easily consider both interval fuzzy number and real number simultaneously. Afterwards, an innovative comparative approach was proposed to compare the three MADM methods, the LI, the I.LI and the NG methods, and to show that which method is more optimal than the other methods. Subsequently, in this thesis, an integration of the NG method and fuzzy multi-objective model was suggested for multi-sourcing and multi-product supplier selection problem. The score of suppliers calculated by the NG method was served as coefficients in one objective function of the multi-objective model. In this fuzzy multi-objective model, the products are divided into two independent and dependent products so that (1) the price breaks (discounts) depend on the size of the order quantities, (2) independent products’ sales volume affect the prices and discounts of the dependent products and (3) all products must be sold as a bundle. Finally, to overcome the third problem, a new weighted additive function, which is able to consider relative importance of each objective as well as condition of fuzzy situation, is proposed to solve the fuzzy multi-objective model and assign optimum order quantities to the suppliers evaluated and ranked by the NG method. The results of the innovative comparative approach showed that the result of the NG method is more optimal than the I.LI method and the latter is more optimal than the LI method. Therefore, the NG method was selected to be integrated with the fuzzy multi-objective model. Also, the fuzzy multi-objective model was solved by the new weighted additive function, and the results demonstrated that besides considering the relative importance of the objectives, the new technique is also able to consider the condition of fuzzy situation

Developing a novel Grey integrated multi-criteria approach for enhancing the supplier selection procedure: A real-world case of Textile Company

upplier selection is one of the most essential activities in purchase management and plays a crucial role in the production phase. Supplier selection as a vital step of supply chain management is a multi-criteria decision-making issue. For any organization, the process of selecting the best supplier holds variable multilayered complications involving quantitative and qualitative criteria. This paper tackles the supplier selection problem in a Turkish Textile Company. The present study carries out a novel grey integrated multi-criteria approach for enhancing the supplier procedure within Textile Company with the help of the grey analytical hierarchy process G-AHP model for weighting the set of criteria, and the grey weighted aggregated sum product assessment WASPAS-G model for prioritizing the suppliers. The study starts with reviewing the previous works of multi-criteria decision-making MCDM methods and the list of existing criteria evaluation in supplier selection. Then, the range of criteria is selected based on the company requirements and the experts’ interview. In the case study, the consistency rate of the models is tested in order to verify the quality of experts’ judgments. The final results affirm that Grey integrated approach could be efficient and far more precise than the existing models for overcoming the supplier selection and evaluation obstacles in the supply chain management

Trading reliability targets within a supply chain using Shapley's value

The development of complex systems involves a multi-tier supply chain, with each organisation allocated a reliability target for their sub-system or component part apportioned from system requirements. Agreements about targets are made early in the system lifecycle when considerable uncertainty exists about the design detail and potential failure modes. Hence resources required to achieve reliability are unpredictable. Some types of contracts provide incentives for organisations to negotiate targets so that system reliability requirements are met, but at minimum cost to the supply chain. This paper proposes a mechanism for deriving a fair price for trading reliability targets between suppliers using information gained about potential failure modes through development and the costs of activities required to generate such information. The approach is based upon Shapley's value and is illustrated through examples for a particular reliability growth model, and associated empirical cost model, developed for problems motivated by the aerospace industry. The paper aims to demonstrate the feasibility of the method and discuss how it could be extended to other reliability allocation models

Use of the TOPSIS technique to choose the best supplier of quarry natural aggregate

Purpose. All over the world, natural substance – the most consumed after water – is the aggregate. The aim of this paper is to select the best supplier of Quarry Natural Aggregate (QNA). Methods. Selection of the best supplier of QNA is performed using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach, and the method of weights based on ordinal ranking of criteria, and Lagrange multiplier. Findings. In this article, the proposed Multi-Criteria Decision Making (MCDM) approach helps the decision maker(s) to choose the best supplier of QNA amongst the considered and evaluated suppliers. Originality. During negotiation with suppliers, many are the decision makers which only attach an importance at two criteria (unit price and quality, or unit price and delivery time). Thereby, other criteria are not taken into account. Consequently, supplier selection would become not-efficient. The originality of this work is based on the multi-criteria approach to choose the best supplier of QNA. Practical implications. The efficient choice of the best supplier of QNA represents a practical and economical value for the enterprises of the civil engineering, public works, railway and hydraulic works.Мета. Обґрунтування та вибір оптимального постачальника кар’єрного щебню як природного заповнювача на основі використання багатокритеріального методу. Методика. Вибір найкращого постачальника кар’єрного природного заповнювача здійснювався за допомогою багатокритеріального методу аналізу варіантів за ступенем близькості до оптимального (TOPSIS) і методу вагових коефіцієнтів на основі порядкового ранжирування критеріїв та множника Лагранжа. Результати. Підхід, що описується в статті, заснований на багатокритеріальному прийнятті рішень і дозволяє обрати кращого постачальника природного заповнювача серед наявних та розглянутих на ринку компаній. В якості ілюстрації запропонована методологія застосована до чисельного прикладу. Це дозволило визначити вагу впливових на оцінку критеріїв, оцінку значень характеристик кожного розглянутого постачальника QNA, встановлення рейтингу розглянутих постачальників QNA і вибір альтернативи {a4} в якості кращого постачальника QNA. Наукова новизна. Вперше для вибору оптимального постачальника природного заповнювача крім факторів ціни і якості встановлено характер впливу на загальну оцінку також ряду інших факторів: вартість транспортування, транспортна відстань, час доставки, гарантійна політика й рівень відхилення. У даній роботі вперше пропонується багатокритеріальний підхід до вибору оптимального постачальника природного заповнювача кар’єра. Практична значимість. Ефективний вибір постачальника природного заповнювача кар’єра важливий з практичної та економічної точок зору для підприємств у галузі цивільного будівництва, громадських робіт, залізниці та гідротехнічних споруд.Цель. Обоснование и выбор оптимального поставщика карьерного щебня как природного заполнителя на основе использования многокритериального метода. Методика. Выбор лучшего поставщика карьерного природного заполнителя осуществлялся с помощью многокритериального метода анализа вариантов по степени близости к оптимальному (TOPSIS) и метода весовых коэффициентов на основе порядкового ранжирования критериев и множителя Лагранжа. Результаты. Подход, описываемый в статье, основан на многокритериальном принятии решений и позволяет выбрать лучшего поставщика природного заполнителя среди имеющихся и рассматриваемых на рынке компаний. В качестве иллюстрации предложенная методология применена к числовому примеру. Это позволило определить вес влияющих на оценку критериев, оценку значений характеристик каждого рассматриваемого поставщика QNA, установление рейтинга рассматриваемых поставщиков QNA и выбор альтернативы {a4} в качестве лучшего поставщика QNA. Научная новизна. Впервые для выбора оптимального поставщика природного заполнителя кроме факторов цены и качества установлен характер влияния на общую оценку также ряда других факторов: стоимость транспортирования, транспортное расстояние, время доставки, гарантийная политика и уровень отклонения. В данной работе впервые предлагается многокритериальный подход к выбору оптимального поставщика природного заполнителя карьера. Практическая значимость. Эффективный выбор поставщика природного заполнителя карьера важен с практической и экономической точек зрения для предприятий в области гражданского строительства, общественных работ, железной дороги и гидротехнических сооружений.The authors thank all the colleagues which have contributed to the realization of this research work

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

Beyond ‘the Beamer, the boat and the bach’? A content analysis-based case study of New Zealand innovative firms

In this paper we will use case studies to seek to understand the dynamic innovation processes at the level of the firm and to explain the apparent 'enigma' between New Zealand's recent innovation performance and economic growth. A text-mining tool, Leximancer, (version 4) was used to analyse the case results, based on content analysis. The case studies reveal that innovation in New Zealand firms can be best described as 'internalised', and the four key factors that affect innovation in New Zealand firms are ‘Product’, ‘Market’, ‘People’ and ‘Money’. New Zealand may be an ideal place for promoting local entrepreneurship, however, many market/technology opportunities cannot be realized in such a small and isolated economy, hence the poor economic performance